SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data and AI at Sigli – “AI for Disabilities: Quick Overview, Challenges, and the Road Ahead”

AI has enormous power in improving accessibility and inclusivity for people with disabilities. This power lies in the potential of this technology to bridge gaps that traditional solutions could not address. As we have demonstrated in the series of articles devoted to AI for disabilities, AI-powered products can really change a lot for people with various impairments. Such solutions can allow users to live more independently and get access to things and activities that used to be unavailable to them before. Meanwhile, the integration of AI into public infrastructure, education, and employment holds the promise of creating a more equitable society. These are the reasons that can show us the importance of projects building solutions of this type.

Yes, these projects exist today. And some of them have already made significant progress in achieving their goals. Nevertheless, there are important issues that should be addressed in order to make such projects and their solutions more efficient and let them bring real value to their target audiences. One of them is related to the fact that such solutions are often built by tech experts who have practically no understanding of the actual needs of people with disabilities.

According to the survey conducted in 2023, only 7% of assistive technology users believe that their community is adequately represented in the development of AI products. At the same time, 87% of respondents who are end users of such solutions express their readiness to share their feedback with developers. These are quite important figures to bear in mind for everyone who is engaged in the creation of AI-powered products for disabilities.

In this article, we’d like to talk about the types of products that already exist today, as well as potential barriers and trends in the development of this industry.

Different types of AI solutions for disabilities

In the series of articles devoted to AI for disabilities, we have touched on types of products for people with different states, including visual, hearing, mobility impairments, and mental diseases. Now, let us group these solutions by their purpose.

Communication tools

AI can significantly enhance the communication process for people with speech and hearing impairments.

Speech-to-text and text-to-speech apps enable individuals to communicate by converting spoken words into text or vice versa.

Sign language interpreters powered by AI can translate gestures into spoken or written language. It means that real-time translation from sign to verbal languages can facilitate communication, bridging the gap between people with disabilities and the rest of society.

Moreover, it’s worth mentioning AI-powered hearing aids with noise cancellation. They can improve clarity by filtering out background sounds, enhancing the hearing experience in noisy environments.

Advanced hearing aids may also have sound amplification functionality. If somebody is speaking too quietly, such AI-powered devices can amplify the sound in real time.

Mobility and navigation

AI-driven prosthetics and exoskeletons can enable individuals with mobility impairments to regain movement. Sensors and AI algorithms can adapt to users’ physical needs in real time for more natural, efficient motion. For example, when a person is going to climb the stairs, AI will “know” it and adjust the movement of prosthetics to this activity.

Autonomous wheelchairs often use AI for navigation. They can detect obstacles and take preventive measures. This way users will be able to navigate more independently and safely.

The question of navigation is a pressing one not only with people with limited mobility but also for individuals with visual impairments. AI-powered wearable devices for these users rely on real-time environmental scanning to provide navigation assistance through audio or vibration signals.

Education and workplace accessibility

Some decades ago people with disabilities were fully isolated from society. They didn’t have the possibility to learn together with others, while the range of jobs that could be performed by them was too limited. Let’s be honest, in some regions, the situation is still the same. However, these days we can observe significant progress in this sphere in many countries, which is a very positive trend.

Among the main changes that have made education available to everyone, we should mention the introduction of distance learning and the development of adaptive platforms.

A lot of platforms for remote learning are equipped with real-time captioning and AI virtual assistants. It means that students with disabilities have equal access to online education.

Adaptive learning platforms rely on AI to customize educational experiences to the individual needs of every learner. For students with disabilities, such platforms can offer features like text-to-speech, visual aids, or additional explanations and tasks for memorizing.

In the workplace, AI tools also support inclusion by offering accessibility features. Speech recognition, task automation, and personalized work environments empower employees with disabilities to perform their job responsibilities together with all other co-workers.

Thanks to AI and advanced tools for remote work, the labor market is gradually becoming more accessible for everyone.

Home automation and daily assistance

Independent living is one of the main goals for people with disabilities. And AI can help them reach it.

Smart home technologies with voice or gesture control allow users with physical disabilities to interact with lights, appliances, or thermostats. Systems like Alexa, Google Assistant, and Siri can be integrated with smart devices to enable hands-free operation.

Another type of AI-driven solutions that can be helpful for daily tasks is personal care robots. They can assist with fetching items, preparing meals, or monitoring health metrics. As a rule, they are equipped with sensors and machine learning. This allows them to adapt to individual routines and needs and offer personalized support to their users.

Existing barriers

It would be wrong to say that the development of AI for disabilities is a fully flawless process. As well as any innovation, this technology faces some challenges and barriers that may prevent its implementation and wide adoption. These difficulties are significant but not insurmountable. And with the right multifaceted approach, they can be efficiently addressed.

Lack of universal design principles

One major challenge is the absence of universal design principles in the development of AI tools. Many solutions are built with a narrow scope. As a result, they fail to account for the diverse needs that people with disabilities may have.

For example, tools designed for users with visual impairments may not consider compatibility with existing assistive technologies like screen readers, or they may lack support for colorblind users.

One of the best ways to eliminate this barrier is to engage end users in the design process. Their opinion and real-life experiences are invaluable for such projects.

Limited training datasets for specific AI models

High-quality, comprehensive databases are the cornerstone for efficient AI models. It’s senseless to use fragmented and irrelevant data and hope that your AI system will demonstrate excellent results (“Garbage in, Garbage out” principle in action). AI models require robust datasets to function as they are supposed to.

However, datasets for specific needs, like regional sign language dialects, rare disabilities, or multi-disability use cases are either limited or nonexistent. This results in AI solutions that are less effective or even unusable for significant groups of the disability community.

Is it possible to address this challenge? Certainly! However, it will require time and resources to collect and prepare such data for model training.

High cost of AI projects and limited funding

The development and implementation of AI solutions are usually pretty costly initiatives. Without external support from governments, corporate and individual investors, many projects can’t survive.

This issue is particularly significant for those projects that target niche or less commercially viable applications. This financial barrier discourages innovation and limits the scalability of existing solutions.

Lack of awareness and resistance to adopt new tools

A great number of potential users are either unaware of the capabilities of AI or hesitant to adopt new tools. Due to the lack of relevant information, people have a lot of concerns about the complexity, privacy, or usability of assistant technologies. Some tools may stay just underrated or misunderstood.

Adequate outreach and training programs can help to solve such problems and motivate potential users to learn more about tools that can change their lives for the better.

Regulatory and ethical gaps

The AI industry is one of the youngest and least regulated in the world. The regulatory framework for ensuring accessibility in AI solutions remains underdeveloped. Some aspects of using and implementing AI stay unclear and it is too early to speak about any widely accepted standards that can guide these processes.

Due to any precise guidelines, developers may overlook critical accessibility features. Ethical concerns, such as data privacy and bias in AI models also complicate the adoption and trustworthiness of these technologies.

Such issues slow down the development processes now. But they seem to be just a matter of time.

Future prospects of AI for disabilities: In which direction is the industry heading?

Though the AI for disabilities industry has already made significant progress in its development, there is still a long way ahead. It’s impossible to make any accurate predictions about its future look. However, we can make assumptions based on its current state and needs.

Advances in AI

It is quite logical to expect that the development of AI technologies and tools will continue, which will allow us to leverage new capabilities and features of new solutions. The progress in natural language processing (NLP) and multimodal systems will improve the accessibility of various tools for people with disabilities.

Such systems will better understand human language and respond to diverse inputs like text, voice, and images.

Enhanced real-time adaptability will also enable AI to tailor its responses based on current user behavior and needs. This will ensure more fluid and responsive interactions, which will enhance user experience and autonomy in daily activities for people with disabilities.

Partnerships

Partnerships between tech companies, healthcare providers, authorities, and the disability community are essential for creating AI solutions that meet the real needs of individuals with disabilities. These collaborations will allow for the sharing of expertise and resources that help to create more effective technologies.

By working together, they will ensure that AI tools are not only innovative but also practical and accessible. We can expect that the focus will be on real-world impact and user-centric design.

New solutions

It’s highly likely that in the future the market will see a lot of new solutions that now may seem to be too unrealistic. Nevertheless, even the boldest ideas can come to life with the right technologies.

One of the most promising use cases for AI is its application in neurotechnology for seamless human-computer interaction.

A brain-computer interface (BCI) can enable direct communication between the human brain and external devices by interpreting neural signals related to unspoken speech. It can successfully decode brain activity and convert it into commands for controlling software or hardware.

Such BCIs have a huge potential to assist individuals with speech impairments and paralyzed people.

Wrapping up

As you can see, AI is not only about business efficiency or productivity. It can be also about helping people with different needs to live better lives and change their realities.

Of course, the development and implementation of AI solutions for disabilities are associated with a row of challenges that can be addressed only through close cooperation between tech companies, governments, medical institutions, and potential end users.

Nevertheless, all efforts are likely to pay off.

By overcoming existing barriers and embracing innovation, AI can pave the way for a more accessible and equitable future for all. And those entities and market players who can contribute to the common success in this sphere should definitely do this.

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Der Beitrag AI for Disabilities: Quick Overview, Challenges, and the Road Ahead erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: iccwbo.org – “Overarching Narrative on Artificial Intelligence”

Artificial intelligence is revolutionising global industries by augmenting human abilities in areas such as language processing, generating creative content, predictive analytics and analytical reasoning, as well as learning and decision-making.

As AI continues to shape economies and societies, a robust governance model becomes essential to harness its benefits while mitigating risks.

ICC outlines the four pillars of global AI governance from the perspective of global business:

1. Principles and codes of conduct
2. Regulation
3. Technical standards
4. Industry self-regulation

Each pillar plays a crucial role in fostering trustworthy, responsible and ethical AI development.

We show, how by adhering to these frameworks, businesses drive innovation, ensure compliance, and build trust, contributing to sustainable and equitable growth.

What is artificial intelligence?

Artificial intelligence is a technology that enables the simulation or extension of human intelligence in machines, allowing them to perform tasks commonly associated with human intelligence, such as speech recognition, content creation, problem-solving, learning, and decision-making, with the potential to boost productivity and augment creativity.

What are the four pillars of global artificial intelligence governance?

As AI continues to evolve, it is essential to strike a balance between realising its full potential for socioeconomic development, while ensuring that it aligns with globally shared values and principles that foster

• equality,
• transparency,
• accountability,
• fairness,
• reliability,
• privacy
• and a human-centric approach.

Over the past decade, this has created an increasingly complex, multi-layered policy environment and a proliferation of policy and regulatory approaches which are sometimes duplicative. These different approaches are gaining rapid momentum, as the technology continues to speed ahead.

The current global governance model for AI is based on four pillars:[…]

Read more: www.iccwbo.org

Der Beitrag Overarching Narrative on Artificial Intelligence erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Zachary Amos – “How AI Can Improve Conflict Resolution in the Workplace”

Artificial intelligence (AI) has emerged as one of the latest employee relations management tools. Human resources (HR) teams and business leaders can use it to resolve conflict faster and more effectively than ever before.

The Importance of Workplace Conflict Resolution

Conflict is an unfortunate side effect of bringing people of all backgrounds together and throwing demands and deadlines in the mix. Most organizations experience it to some extent. In fact, nine in 10 professionals say they’ve worked with a “toxic” person in the past five years. This issue can diminish productivity and dampen employees’ positive moods.

Over time, workplace conflict results in noticeable productivity losses. In the United States, employees spend 2.1 hours in conflict per workweek, which amounts to 385 billion lost workdays. The involved parties, HR team and upper management all lose valuable time when focusing on resolving the dispute.

Types of AI Businesses Can Use in Conflict Resolution

AI has emerged as an effective tool for conflict resolution. Business leaders and HR professionals don’t have to stick to a standard machine learning model to ensure success — there are numerous types to choose from.

The main types of AI businesses can use for conflict resolution include:

• Facial recognition: AI-powered cameras can recognize and analyze faces, enabling them to monitor employees.
• Natural language processing (NLP): An NLP algorithm can understand, interpret and mimic language. It can comprehend context and carry a conversation.
• Generative AI: Generative AI can create original images, text or audio based on users’ prompts.
• Chatbot: A chatbot can hold conversations with dozens of employees simultaneously. It will understand them regardless of their language or writing style.
• Speech recognition: Speech recognition AI can turn audio into text. Some models can analyze the finished product to identify the speaker’s emotional state.
• Personal assistant: A personal assistant AI is similar to a chatbot but can handle complex questions and commands. Its applications are much more broad.

Each type of AI has unique strengths and weaknesses, so strategic selection is essential. Decision-makers should choose the one that best meets their workplace’s needs and employees’ technical skills.

The Benefits of Addressing This Issue With AI

Most HR professionals rely on outdated conflict resolution strategies like digital tables or paper-based systems. In 2023, 66% of organizations said they’d transition from using spreadsheets and generic databases for employee relations management in 2024.

Many businesses have decided AI will be their conflict resolution tool of choice moving forward. According to a 2022 survey, 94% of business leaders agree it is essential for success. Since it’s so versatile, virtually any industry can use it for workplace-specific purposes.

Many workplaces are already using some kind of AI. Aover 30% of businesses have integrated generative models into their processes. Since they’re already familiar with the technology, implementing it for conflict resolution will be straightforward.

AI specializes in speed and accuracy — it can process tens of thousands of words in seconds. Since one of the most significant impacts of workplace conflict is lost workdays, businesses would benefit significantly from expediting their resolution process.

Another one of the biggest benefits AI has that most other conflict resolution tools don’t is adaptation. Machine learning models evolve as they process new data, making them essentially future-proof — businesses can keep using them regardless of whether they hire new employees or the source of conflict changes.

AI’s Role in Conflict Resolution in the Workplace

There are multiple ways AI can improve the typical conflict resolution process.

Predict When Conflicts Will Arise

AI can essentially predict the future if it analyzes historical and current data simultaneously. Since it recognizes trends invisible to the human eye, its forecasts are more accurate than anything an HR professional could come up with.

Businesses can use various AI tools to analyze personality traits, behavioral cues, speech patterns and written communication. This way, they can anticipate employees’ emotional states to tell when workplace conflict is about to break out and step in before anything happens.

Bridge Cultural Barriers

Since communication differences are responsible for 39% of workplace conflicts, an NLP AI would be ideal for most conflict resolution strategies. It can bridge cultural and language barriers, ensuring employees avoid miscommunications.

Provide Support to HR Teams

Chatbots, personal assistants and generative AI models can support HR teams by walking them through conflict resolution strategies, summarizing the dispute or explaining how each party wants to be treated.

Mediate Between Parties

Around four in 10 employees don’t report workplace misconduct or harassment. Of those who do, 61% go to their manager instead of to HR — which can lengthen the time resolution takes. A chatbot can eliminate this hiccup by acting as a neutral mediator.

Chatbots aren’t biased against certain employees and aren’t personally invested in workplace conflict, so they’re the ideal mediators. They can suggest resolutions, generate apologies or reflect on the situation, helping both parties engage in a constructive conversation.

Identify Sources of Conflict

While communication differences and unclear job responsibilities are typical sources of workplace conflict, every business is different. AI can help HR professionals identify hidden trends and narrow down the root of their problems.

AI’s Impact on Workplace Conflict Resolution

Businesses using AI for conflict resolution can prevent workplace disputes from happening, accelerate the mediation process and encourage employees to settle their differences on their own. As a result, they gain a happier, more productive workforce.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.

Der Beitrag How AI Can Improve Conflict Resolution in the Workplace erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Sahev Karmakar – “How AI Search Engines Are Revolutionizing Information Retrieval”

Since the dawn of the internet, AI search engines have played a crucial role in information retrieval, beginning with Archie, the first AI engine in the early 1990s designed to locate files on FTP sites 1. Today, the landscape has evolved significantly with the advent of generative AI and machine learning technologies. These advancements have made AI search engines like Google, Bing AI, and others powered by GPT-4 and Perplexity AI, more efficient at understanding and processing language on a level nearly indistinguishable from human capabilities.

The integration of generative AI into search engines is not just a leap forward; it’s revolutionizing how we retrieve information online. With capabilities spanning from SEO-optimized content to context-rich input processing, AI search engines now offer a more intuitive and efficient search experience. This article will delve into the transformative power of generative AI in search technologies, exploring how it enhances information retrieval and the potential challenges and opportunities that lie ahead in this rapidly evolving field.

The Evolution of Search Engines

The evolution of search engines has been a remarkable journey, marked by significant milestones and technological advancements. Here’s a brief overview:

The Dawn of Search Engines:

• Archie (1990): Considered the first search engine, Archie was developed by Alan Emtage at McGill University, designed to index FTP archives to make finding files easier 3.
• W3Catalog (1993): As the web’s first primitive search engine, W3Catalog utilized web robot data to create its listings, marking a significant step towards more sophisticated search technologies 4.
• WebCrawler (1994): This was the first search engine to index entire pages, setting a new standard for how search engines operated henceforth 6.

Revolutionary Algorithms and Models:

• PageRank Algorithm (1998): Google’s introduction of the PageRank algorithm revolutionized search by ranking pages based on the quality and quantity of links pointing to them, significantly improving search result quality 3.
• BERT Algorithm (Recent Years): Google’s BERT uses natural language processing to better understand the intent behind searches, moving beyond simple keyword matching to a more nuanced understanding of queries 1.

Generative AI and Search Engines:

• Generative Adversarial Networks (2014): The introduction of GANs and subsequent advancements in transformers and large language models have paved the way for generative AI in search, enabling AI search engines to generate more accurate, contextually relevant search results 2.
• Modern AI Search Engines: Today, engines like Google Search, Bing, and those powered by GPT-3 are integral parts of the internet, used by millions daily, showcasing the evolution from basic file indexing to complex, AI-driven search processes 1.

This progression underscores the transformative impact of AI and machine learning on the field of information retrieval, setting the stage for future innovations.

Generative AI in Search: How It Works

Generative AI in search engines significantly enhances the user experience by employing a combination of natural language processing (NLP), machine learning (ML), and deep learning technologies. These AI components work together to interpret and process a user’s search queries in a more human-like manner, providing results that are not only relevant but also contextually rich and informative9. For example:

• Natural Language Processing (NLP): Enables the search engine to understand the context and nuances of user queries, going beyond mere keyword matching15.
• Machine Learning (ML): ML algorithms learn from vast datasets to improve the search engine’s ability to rank pages more accurately according to the relevance of the search query16.
• Deep Learning: Employs neural networks to understand patterns in data, allowing for the generation of new, similar data, which can be particularly useful in predicting user intent and providing personalized search results11.

Furthermore, generative AI models like ChatGPT, Google Bard, and DALL-E are pivotal in this evolution, undergoing iterative training to refine their outputs. This training enables these models to generate unique and original content across various domains, mimicking human creativity and providing users with insights and information that may not be readily available on the web13. Through these advanced AI technologies, search engines are now capable of offering a more intuitive, efficient, and personalized search experience, revolutionizing the way information is retrieved online91213.

Case Studies: Generative AI Transforming Information Retrieval

Since the release of ChatGPT in November 2022, generative AI has seen rapid advancements, with new iterations emerging several times a month. This technology has the capability to create diverse content types, including written, image, video, audio, and coded content16. Businesses are leveraging these tools to develop applications that address specific industry and function needs, offering more value than general applications16. This trend is evident in various sectors:

Google’s introduction of Generative AI capabilities to its search function marks a significant milestone. The Search Generative Experience (SGE) allows for conversational interactions, providing AI-driven synopses and suggesting follow-up actions based on initial queries. This feature, tailored for the Indian market, includes language switching between English and Hindi and Text-To-Speech technology, catering to auditory learners17. Additionally, SGE is designed to aid coders and programmers in code comprehension and troubleshooting, showcasing Google’s commitment to implementing generative AI responsibly and maintaining stringent quality standards17.

Challenges and Limitations

Despite the transformative potential of AI in search engines, several challenges and limitations persist:

Bias and Availability:

• AI search engines may exhibit bias if trained on skewed data, potentially leading to unfair outcomes.
• Limited language and regional support can restrict access and utility across diverse global communities 16.

Technical and Financial Constraints:

• Dependence on sophisticated technology that may be susceptible to disruptions 16.
• High costs associated with development and maintenance, posing a barrier for smaller entities 18.

Accuracy, Privacy, and Ethical Concerns:

• Inaccurate results may arise from poor-quality training data, undermining reliability 16.
• Privacy issues due to extensive data collection required for AI functionality, raising significant concerns among users 18 21.
• Ethical dilemmas, including the potential for misinformation and copyright infringement, necessitate vigilant regulatory oversight 1.

These challenges underscore the need for ongoing research, ethical considerations, and technological advancements to fully harness the potential of AI in search engines while mitigating its limitations.

The Future of Search with Generative AI

The future of search with generative AI is poised to revolutionize how we interact with digital information, offering unprecedented personalization and efficiency. Key areas of transformation include:

Personalized Search Experience:

• AI-driven personalization will enhance Google Search, tailoring results to individual user behaviors and preferences, significantly refining the relevance of search outcomes.
• Voice search and NLP advancements will facilitate hands-free interactions and comprehend spoken queries with remarkable accuracy, making search more intuitive 23.

Impact on Industries:

• Generative AI’s contribution to the global economy could reach up to $4.4 trillion annually, with high tech and banking sectors benefiting immensely from accelerated software development processes.
• Marketing, sales, and other fields will similarly see substantial gains, leveraging gen AI for improved operational efficiency and customer engagement 16.

Operational and Business Enhancements:

• Customer support, multilingual interactions, and conversational databases will see significant improvements through generative AI, enhancing user experiences across various touchpoints.
• Enterprises will witness advancements in cybersecurity, business intelligence, and AIOps, driving innovation and efficiency in critical operational areas 24.

These developments underscore the transformative potential of generative AI in search technology, heralding a new era of information retrieval that is more personalized, efficient, and intuitive.

Conclusion

Through the journey from the inception of Archie to the sophisticated AI-driven search engines of today, the evolution of information retrieval technology underscores a monumental transition in how we access and interact with information. The transformative power of generative AI has not only augmented the efficiency and intuitiveness of search engines but also introduced a new era of personalized information discovery that resonates with my personal experiences in the field. Seeing these technological advancements firsthand has reinforced the notion that we are on the cusp of a revolution that’s reshaping the fabric of digital information retrieval.

Reflecting on the discussed challenges and the potential of generative AI, it’s evident that while we navigate through the complexities of bias, privacy, and ethical concerns, the horizon is bright with opportunities for enhanced personalization, operational improvement, and a more intimate connection with the digital world. As we continue to embrace these advancements, further research and responsible implementation will be pivotal in realizing the full promise of AI in search technologies. My journey and observations in the tech landscape echo a sentiment of excitement and caution, underscoring the importance of harnessing AI’s power to foster innovation while diligently addressing its limitations.

References

[1] – https://searchengineland.com/ai-future-search-436277
[2] – https://www.techtarget.com/searchenterpriseai/definition/generative-AI
[3] – https://topofthelist.net/a-history-of-search-engines/
[4] – https://en.wikipedia.org/wiki/Search_engine
[5] – https://www.oslash.com/blog/history-evolution-of-web-search
[6] – https://www.libertymarketing.co.uk/blog/a-history-of-search-engines/
[7] – https://www.researchgate.net/publication/265104813_History_Of_Search_Engines
[8] – https://www.webfx.com/blog/seo/generative-ai-in-search/
[9] – https://www.linkedin.com/pulse/future-search-generative-ai-kevin-watts
[10] – https://blog.google/products/search/generative-ai-search/
[11] – https://searchengineland.com/what-is-generative-ai-how-it-works-432402
[12] – https://theincmagazine.com/the-future-of-search-is-here-how-generative-ai-will-transform-your-search-strategy/
[13] – https://hgs.cx/blog/how-to-use-generative-ai-for-data-extraction-and-analysis/
[14] – https://arxiv.org/abs/2311.18550
[15] – https://www.kth.se/en/biblioteket/soka-vardera/sok-och-vardera-info/ai-och-informationssokning-1.1288865
[16] – https://www.mckinsey.com/featured-insights/mckinsey-explainers/whats-the-future-of-generative-ai-an-early-view-in-15-charts
[17] – https://www.linkedin.com/pulse/revolutionizing-search-googles-generative-ai-elevates-information-xh2hf
[18] – https://searchanise.io/blog/ai-powered-site-search/
[19] – https://www.linkedin.com/pulse/challenges-limitations-ai-generated-content-pradeep-kumar
[20] – https://www.mikksanetwork.com/en/artificial-intelligence-in-seo-advantages-and-disadvantages/
[21] – https://www.adlift.com/in/blog/understanding-the-disadvantages-of-using-ai-in-digital-marketing/s/
[22] – https://glair.ai/post/5-biggest-limitations-of-artificial-intelligence
[23] – https://aicontentfy.com/en/blog/maximizing-efficiency-how-google-search-revolutionizes-information-retrieval
[24] – https://www.techtarget.com/searchenterpriseai/feature/The-future-of-generative-AI-How-will-it-impact-the-enterprise
[25] – https://www.linkedin.com/pulse/impact-ai-advancements-search-engines-seo-advertising-prakash
[26] – https://www.glean.com/blog/enterprise-ai-search-rag

About the Author:

Sahev Karmakar, the inspiring Founder and Chief Editor of LearnReal.in, holds a Master of Science degree in Applied Mathematics with Computer Programming and Oceanology (Specialized in Operations Research) from Vidyasagar University, Midnapore. He also did a Bachelor of Education from WBUTTEPA. He has 5+ years of experience in educational content creation.

Der Beitrag How AI Search Engines Are Revolutionizing Information Retrieval erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: ibm.com – “Conversational AI Use Cases For Enterprises”

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. This sophisticated foundation propels conversational AI from a futuristic concept to a practical solution.

Several natural language subprocesses within NLP work collaboratively to create conversational AI. For example, natural language understanding (NLU) focuses on comprehension, enabling systems to grasp the context, sentiment and intent behind user messages. Enterprises can use NLU to offer personalized experiences for their users at scale and meet customer needs without human intervention.

Natural language generation (NLG) complements this by enabling AI to generate human-like responses. NLG allows conversational AI chatbots to provide relevant, engaging and natural-sounding answers. The emergence of NLG has dramatically improved the quality of automated customer service tools, making interactions more pleasant for users, and reducing reliance on human agents for routine inquiries.

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. ML algorithms understand language in the NLU subprocesses and generate human language within the NLG subprocesses. In addition, ML techniques power tasks like speech recognition, text classification, sentiment analysis and entity recognition. These are crucial for enabling conversational AI systems to understand user queries and intents, and to generate appropriate responses.

DL, a subset of ML, excels at understanding context and generating human-like responses. DL models can improve over time through further training and exposure to more data. When a user sends a message, the system uses NLP to parse and understand the input, often by using DL models to grasp the nuances and intent.

Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends. ML and DL lie at the core of predictive analytics, enabling models to learn from data, identify patterns and make predictions about future events.

These technologies enable systems to interact, learn from interactions, adapt and become more efficient. Organizations across industries increasingly benefit from sophisticated automation that better handles complex queries and predicts user needs. In conversational AI, this translates to organizations’ ability to make data-driven decisions aligning with customer expectations and the state of the market.[…]

Read more: www.ibm.com

Der Beitrag Conversational AI Use Cases For Enterprises erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data Science at Sigli – “How People With Cognitive Disabilities Can Benefit From AI-Powered Solutions”

Cognitive disabilities are among those things that people prefer not to discuss, especially when they have faced them in their families. But it doesn’t mean that this topic should stay without social attention. Vice versa, it can be viewed as an alarming sign that these people do not receive enough support. And it is one of the main key indicators that show us how important it is for society to find tools, solutions, and approaches that will help people with cognitive disabilities and their families cope with related difficulties.

Cognitive disabilities: Basics

So, what do we mean when we mention cognitive impairments? This term is used in relation to a wide range of conditions. It includes but is not limited to mental illnesses, autism spectrum disorders, intellectual disability, brain injuries, Down syndrome, Alzheimer’s disease, and other dementias.

These conditions can greatly affect various cognitive skills, such as attention, short-term and long-term memory, logic, and reasoning. Among other issues, we should also mention the ability of people’s brains to handle different types of information. While there are states that affect math or language processing, some others can affect brain processing abilities even in a more severe way which will prevent people from general understanding of reality and the world around them.

The impact that cognitive disorders have on people’s lives can be different, depending on the type of disorder that we are talking about and its severity. While some disorders may stay practically unnoticed by other people, in some cases they may have a strong influence on individuals’ ability to communicate and interact with their surroundings. Their speech, behaviors, and reactions to different events may seriously differ from social norms. They may have problems with fulfilling even simple routine tasks. Such conditions lead to their dependence on their tutors and families while the lack of proper control and assistance may result in negative consequences for their health and even lives.

It means that when we are speaking about supportive tools for people with cognitive impairments, we should also talk about solutions for those who take care of them, who teach them, who help them with their everyday tasks because it is very hard work. But we are quite sure that modern technologies can be of great help in this context.

In one of our previously published articles, we discussed the power of Artificial Intelligence in making the learning process a more enjoyable journey for both students with learning difficulties, such as dyslexia, and their teachers. And in this article, we offer you to consider how AI can help to facilitate a lot of processes for people with cognitive impairments, their families, nurses, and tutors who directly interact with them.

Traditional methods vs AI-powered tools

Working with people with cognitive disabilities requires a comprehensive and personalized approach. Traditional solutions are aimed at enhancing people’s independence, developing their communication and social skills, and increasing their overall quality of life. Among these traditional methods, it’s worth mentioning educational therapy with a focus on gamification, behavioral therapy, speech therapy, and occupational therapy. All these approaches presuppose the active participation of tutors and their holistic involvement in all the processes. In their work, they use such assistive tools as memory aids, visual charts and schedules, picture boards, reminders, etc.

The level of efficiency of all the traditional methods may vary depending on the exact disability, its severity, as well as the skill and qualifications of those specialists who work with people with cognitive impairments. Of course, their contribution and efforts can’t be underestimated.
Nevertheless, we strongly believe that AI-powered tools can greatly increase the efficiency of therapies, optimize the load for tutors and nurses, and make it possible for people with cognitive disabilities to live independently (or at least safely perform a limited set of tasks without external help). All this is possible thanks to the possibility of finding an individualized approach to each person, automating a lot of processes, and conducting a more advanced analysis of symptoms and behavioral patterns.

Let’s proceed to a more detailed overview of AI use cases in the work of people with cognitive impairments.

Advanced research on skills and behaviors of people with autism

One of the main problems that the healthcare industry has to deal with today is the risk of omitting small facts that may have a serious impact on the correct diagnostics. Unfortunately, some details can’t be noticed in a huge volume of information and then processed by a human. However, modern AI tools can successfully address this issue. They can detect even the slightest signals that can be signs of particular disorders and provide doctors with a comprehensive overview of the case.

Very often it may become a real challenge to identify traits of autism, especially in those cases when a child doesn’t need any specific support from adults in everyday tasks. Sometimes doctors need months or even more to get a diagnosis. But the later a diagnosis is confirmed, the later therapies begin which may lead to undesirable consequences.

But AI (and precisely, deep learning) tools are known for their capacity to spot patterns which can be extremely helpful for making the right decision.

One of such solutions is a system called the Naturalistic Observation Diagnostic Assessment launched by an Idaho-based company Behavior Imaging. The company offers an application that provides parents with all the required features for uploading videos of their children to analyze their behavior in a remote format. Behavior Imaging has already started training AI-like algorithms that will be able to categorize behaviors and provide hints to clinicians. It is not expected that the system will make decisions on its own but it will support specialists in their work.

Another example of using AI is creating robots that will interact with children with autism spectrum disorders. They can help kids build social interactions, provide relevant responses in different communicative situations, and identify different facial expressions.

Moreover, today there are already various AI apps that can analyze the skills, emotions, and needs of users and provide personalized practices with step-by-step lists. Though there can be an opinion that their efficiency is lower than what the use of special robots can offer, they have other benefits. In comparison to robots, they are more affordable and easy to use in schools and at home.

AI-powered solutions for people with dementia

As well as in the previously described case, AI is very useful for the early detection of dementia and understanding the pace at which symptoms develop. This knowledge is crucial for appropriate treatment.

But that’s not the only AI use case. One of the main tasks that doctors have in their struggle with dementia is to help people maintain their independence for as long as possible. And here is when supportive tools enter the game.

Today researchers are investigating the possibility and feasibility of mounting sensors around the house to track people’s behavior. If any signs of risky patterns are detected, they will get immediate help. For example, home appliances will be automatically turned off or a nurse will be notified.

AI tools can also provide cognitive support by offering prompts for social interactions or reminders for daily tasks.

Breaking down communication barriers

We’d like to start with an example that is well-known to a very wide audience. It’s highly likely that you’ve also seen the solution used by Stephen Hawking for talking. Due to Amyotrophic Lateral Sclerosis, he lost the ability to express his thoughts verbally and could communicate with the help of a speech-generating device (SGD). It could be controlled just with a single cheek muscle. Using this muscle, Hawking selected words and phrases and then they were synthesized into speech practically immediately.

This technology is rather expensive which means that it is not available to everyone. Nevertheless, today there are more affordable alternatives like speech-to-text and text-to-speech tools that are already widely used by people with visual and hearing disabilities. However, not all mental states can allow people to use them.

Another case that can be mentioned in this category is Voiceitt. It is an AI-based tool for augmentative and alternative communication. Thanks to speech recognition technology and AI models, the app can translate unintelligible, non-standard sounds into clear words. As a result, people who have verbal language production disabilities, including those caused by Down syndrome, can communicate with others in real-time.

Personalized learning

This AI use case plays a vital role when it comes to tutors and their work.

Educational tools powered by AI can have the relevant functionality for creating specific learning programs based on the individual needs of people with cognitive disabilities. These tools can offer tailored lessons, addressing the strengths and challenges of each person. As a result, it can greatly facilitate such tasks for tutors.

Moreover, some AI-based educational applications can be intended for independent use by children and adults with cognitive impairments if their skills allow them to do it.
With the right training, AI models can demonstrate impressive results in delivering individualized learning programs. That’s why this sphere definitely deserves more focused exploration.

Final word

In this series of articles, we are talking about the capacity of artificial intelligence to change the lives of people who face any physical or mental disorders, to help them integrate into society, and enjoy more opportunities that earlier used to be inaccessible to them.

While working with people with cognitive disabilities can be a very sensitive and challenging process, AI is one of the most promising technologies in this field. AI-powered solutions can efficiently analyze huge volumes of data, which is important for making the right diagnosis, choosing therapy, and finding the right approach for each person.

If you have any ideas for such kind of solutions, at Sigli, we will be always happy to cooperate with you and help you with your project realization.

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Der Beitrag How People With Cognitive Disabilities Can Benefit From AI-Powered Solutions erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data Science at Sigli – “Dancing With Letters Or When Dyslexia Challenges People And Technologies.”

We want to help learners with special needs to cope with difficulties that they typically face in the education process. In this article, we’d like to talk about one of the problems in education that is often underestimated – the lack of adequate solutions and learning methods for people with dyslexia.

What is dyslexia?

The British Dyslexia Association (BDA) defines dyslexia as “a learning difficulty that primarily affects the skills involved in accurate and fluent word reading and spelling”.

Today, around 15-20% of the world’s population is affected by dyslexia. In other words, approximately 1 in 5 individuals suffer from some form of this learning difficulty.

Though some signs of dyslexia may be noticed even when a child is very small (these toddlers may start talking later than others), let us mention those symptoms that are common among older children, teenagers, and adults:

• Difficulty reading and spelling;
• Problems telling apart parts of speech;
• Trouble learning different letters, especially those that have similar shapes (like “b” and “d”);
• Difficulty learning how different sounds go together and their correct order in a word;
• Trouble pronouncing new words.

Despite a stereotype, dyslexia shouldn’t be associated with low intelligence. It can happen regardless of the intellectual level that a person has. It means that it doesn’t affect the cognitive functions of individuals. And this idea should be made widely known, especially within the sphere of education. Students with dyslexia can demonstrate amazing academic results, they have excellent visual, spatial reasoning, and analytical skills. However, for solving some tasks they may need to apply more effort than students who don’t have learning difficulties.

Quite often barriers in learning appear when teachers do not have the possibility to address the existing issues in a proper way. That’s why while thinking about solutions that can facilitate the learning process for people with dyslexia, it is also worth considering various tools that can help teachers with them.

How AI helps to deal with difficulties caused by dyslexia

At Sigli, we have deeply studied the possibilities to apply Artificial Intelligence tools for addressing the problems caused by dyslexia in learning. And we have already delivered a couple of products with such goals for our customers.

Though there are some limitations in this sphere that we are going to discuss further in this article, AI has turned out to be a reasonable choice for building solutions for students with dyslexia. AI-powered products can help users overcome limitations related to their difficulties with spelling, grammar, and syntax and to fully open their potential in learning.

Visual and voice aids

Visual and voice support for reading is a very useful thing for learners with dyslexia. When a user is reading a text it can be also automatically voiced and highlighted within the process. In such a way a person will have the possibility of not only listening to the text but also having a look at how different words are spelled and pronounced. Modern solutions can also offer definitions for words that are unknown to a person. When a user doesn’t know a word, he or she can just click on it and get an explanation.

Moreover, Artificial Intelligence can visualize written information. It can support words with images which makes it easier for learners with dyslexia to remember them. One of the examples of such solutions is Microsoft’s Immersive Reader.

Personalized exercises

For people with dyslexia, it is required to invest more time and effort in practice. For example, they need to fulfill various exercises that help them better understand the difference between various parts of speech. For teachers, it can be rather challenging to prepare the required number of exercises for students. And AI can do it for them. Teachers will just need to formulate their inquiry and Artificial intelligence can generate unique exercises based on the student’s needs and requirements.

Complexity level estimation

AI-powered solutions can be of great help for self-education and self-preparation for students with dyslexia. As reading causes difficulties, it may require a lot of time, the exact amount of which may depend on the complexity of the text itself. It is practically impossible to estimate the complexity of the text without reading and predict how much time you need to spend on working with it. That’s why it is a good idea to implement such AI tools that will analyze the complexity of written content to let users decide whether they are ready to start reading the text based on the time required for it.

Context word prediction

When people with dyslexia need to write a text, this task may also take too much time and turn out a very irritating process. What’s more, it may be practically impossible to avoid mistakes in spelling. As a result, students may be fully discouraged. But AI can contribute to solving this problem, at least when they are typing texts on their laptops, tablets, or smartphones. AI can analyze the context and predict the following word. All that users will need to do is just to choose the best variant from the offered options.

On one hand, somebody may say that AI will kill creativity and people won’t use their imagination at all. On the other hand, we insist that AI can help people with dyslexia to stop being afraid of expressing themselves which is even more important for the learning process.

Text summarization

Sometimes we do not need to read a text attentively to get all the details. It may be enough just to look through it to grasp the main idea. Let’s admit a lot of students regularly do this to save time. Unfortunately, this trick doesn’t work for those who have dyslexia. But AI can be also helpful in this case. It can process a long text and provide its short summary that will contain the main idea.

Supportive tools: Grammar checkers and voice assistants

Speaking about solutions for learners with dyslexia, we can also mention some tools that are known and widely used by a very wide audience, including those people who do not have learning difficulties. That’s writing assistance and grammar checkers like ChatGPT or AI-powered Grammarly tools that can help users correct errors in their texts and can even provide real-time recommendations on text enhancements. Thanks to such tools, students can fully focus on the content of their texts while AI will help them avoid grammar and spelling mistakes.

Well-known Alexa and Siri (or any similar solutions) can also be very helpful for students with dyslexia. Instead of typing their requests for any information (which can become a rather time-consuming process), people can interact with such solutions using voice commands. These voice assistants can also read the necessary information for students so that they won’t need to do it on their own if they have difficulties with it. As a result, as well as in the previous case, they can concentrate more on the information itself instead of worrying about how to read the required texts.

Challenges for using AI to help people with dyslexia

If you asked us whether AI is a good choice for addressing the issues that people with dyslexia face in learning, our short answer would be “definitely yes”. However, we should admit that in this aspect, there are still some challenges that require serious attention from the side of developers. And we’d like to draw your attention to them.

First of all, AI-powered solutions can’t fully eliminate the necessity of human involvement. and it doesn’t matter whether we are talking about creating special personalized tasks and learning plans for students with dyslexia or about writing some type of content like essays, for example. AI is a great tool. It can help teachers in their work but it can’t fully replace a teacher. It can help students but it can’t do everything instead of them (but in general, it is even okay as to learn something people need to invest their own efforts in this process). It means that even if you have the best AI solution, you still need to control and manage its work.

And the second point here is the limitations related to the use of AI in testing solutions that help to detect whether a person has dyslexia or similar symptoms are a consequence of other issues. Already now such solutions are available. They are enriched with natural language processing, speech recognition tools, as well as ML algorithms. These technologies can detect patterns in the behavior of a person that may be signs of dyslexia.

Of course, such tools can successfully complement traditional diagnostics methods and reduce the time that is typically required for this process. Nevertheless, there are still a lot of concerns related to their reliability. Moreover, we shouldn’t forget about ethical factors. Is it really ethically correct to let AI deeply study and analyze the behavior of individuals and accumulate data about them from different sources? This question remains to be rather disputable.

The existence of the mentioned challenges doesn’t mean that such problems can’t be solved. They can be and should be solved and already now the work on them is being conducted. It is expected that in the future such solutions will become more powerful and efficient. And it will be possible to fully rely on them. However, now it is too early to do it.

Final word

As you can see, today artificial intelligence can be successfully applied to enhance the process and quality of education for everyone, including those people who face learning difficulties.

It can help learners spend less time on some basic things that they have issues with, like reading, and concentrate more on core learning activities like studying new information or solving the set tasks. Quite often such learning difficulties as dyslexia and their impact are ignored. However, AI provides us with a chance to stop closing our eyes to these issues and finally create a learning environment that will be comfortable for everyone.

In the next article, we will share some insights that our Sigli team gained while working on the development of an AI-powered dyslexia compensation solution. Stay tuned!

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Artem will be speaking at the SwissCognitive World-Leading AI Network AI Conference focused on The AI Trajectory 2024 – Invest for Impact on 13th December.

Der Beitrag Dancing With Letters: When Dyslexia Challenges People And Technologies. erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Aron Kantor – Editor of TheBusinessDive

One thing is certain: AI assistants change businesses’ workflows and can make internal processes more effective than ever. In this article, I will dive into how AI assistants can boost a business’ effectiveness in many areas.

Key takeaways

• AI coding assistants lead to faster and safer coding, which can elevate the overall quality of developers’ work.
• Utilizing AI during content creation can enhance your abilities and help you work smarter, faster, and more effectively.
• You can entirely automate your online meetings using AI to focus on more crucial tasks.
• AI personal assistants are excellent for boosting your productivity and keeping yourself organized.
• A business can use AI to optimize legal processes, providing cost savings, improved accuracy, and enhanced efficiency.

What is an AI assistant?

Essentially, an AI assistant can be any digital tool or application that utilizes generative AI technologies to perform specific tasks, answer questions, or carry out commands.

Generative AI models use text input for text generation, image generation, video creation, or music composition. AI assistants are able to learn from past interactions due to machine learning, which improves the accuracy of their responses over time.

In general, you can interact with generative AI tools in two ways. An AI assistant can understand voice commands using natural language processing for speech recognition. Furthermore, AI assistants are capable of understanding text messages.

For example, Siri uses following orders based on voice commands, while ChatGPT understands text messages.

AI coding assistant

Code writing is one of the areas where AI assistants can be deployed effectively, and their machine-learning skills can be a great asset. An AI coding assistant can help in two ways for the developers.

First, it can generate code based on prompts, which can significantly decrease the time requirements of coding. Secondly, AI coding assistants suggest code for auto-completion while developers write code in real-time.

Microsoft’s research shows developers can perform coding 55.8 percent faster when using an AI assistant. Considering the average salary of one developer, an AI coding assistant can be a game-changer in terms of cost-efficiency.

Generating code based on prompts and offering real-time auto-completion suggestions helps developers focus on higher-level logic and problem-solving. This expedites the coding process and reduces the chances of errors.

Ultimately, AI coding assistants lead to faster and safer coding, which can elevate the overall quality of developers’ work. However, it is essential to emphasize that AI can only support developers and does not replace them.

AI writing assistant

Content creation is a lengthy process and requires patience and inspiration. The question is how long it takes to create a single blog post, depending on multiple factors. Creating a single blog post can take an average of two to five hours.

However, the time spent on a single blog post is also impacted by how much research is necessary and your topic, and do not forget the brainstorming part of the work. For example, creating a thorough blog post takes me approximately 6 to 10 hours. Besides crafting my post, I spend between 4 and 6 hours finding the right topic and researching.

You see, quality work requires sufficient time, but not least, inspiration.

One of the greatest strengths of AI writing assistants is that they can decrease the time spent on first drafts. An AI writer assistant can save anywhere between 2-4 hours on a 1000-word blog. The time you can save also depends on various factors, but one thing is sure: it will greatly accelerate the process.

In a nutshell, an AI writing assistant helps you create more content in less time. An AI writing assistant alone still cannot generate that level of value that a human is capable of. Instead, it acts as a catalyst to enhance your abilities and work smarter, faster, and more effectively.

AI meeting assistant

Believe it or not, meetings take up an average of 15% of a business’s collective time. Unproductive online meetings can not just be a waste of time but also a waste of money.

Businesses with less than 50 employees spend an average of $18,000 annually on unproductive meetings, while businesses with over 100 employees spend an average of $420,000 annually on unproductive meetings.

AI meeting assistants or AI meeting managers can help you in many ways to reduce wasted money and time to make you more productive.

Depending on the specific AI app, it generally helps you with the following tasks:

• Recording meeting,
• Taking notes,
• Prepares meeting summaries,
• Meeting analysis,
• Automated meeting scheduling,
• It helps you to find relevant information more easily in your meeting notes.

Overall, an AI meeting manager can fully automate your online meetings and help you focus on more crucial tasks.

AI personal assistant

An AI personal assistant is software designed to understand natural language voice and text commands and carry out tasks for the users. They primarily support an individual’s daily activities, work, or lifestyle.

An AI personal assistant is a great solution to boost your productivity. It can help you control your smart devices, send messages, make phone calls, and keep you organized.

Moreover, it can perform tasks mostly handled by human personal assistants or secretaries in the past. In this way, businesses can take one step further in digitalization while reducing costs.

AI legal assistant

Let’s find out how AI legal assistants can optimize businesses’ legal processes.

Contract management

According to the Enterprise Legal Reputation (ELR) Report by Onit, 40% of legal teams spend half of their workday reviewing and handling contracts. While legal teams handle many contracting processes, almost every team is exposed to poor contract management.

AI legal tools can help you manage and automate workflows across the entire contract lifecycle. These AI solutions can extract key details from the contract, like expiration dates, important clauses, or categories, using machine learning.

Legal research

The legal research is a time or money-consuming process, or sometimes both. You can either do it for yourself if you have the necessary expertise or hire a lawyer.

However, AI can be a game-changer in terms of legal research. AI tools are capable of effectively handling huge amounts of data. These tools can dive into researching regulations, caselaw, secondary sources, and more to provide you with all the details you might need.

Workflow automation

AI-powered legal tools offer several advantages regarding workflow automation. It can reduce errors, accelerate contract creation and document assembly, and decrease contract preparation costs.

AI can give you a hand in various tasks, such as automated contract review, approval, and automated renewal, ultimately simplifying the contracting process.

Endnote

As with all disruptive technology, AI is very divisive. While it is tempting to be skeptical and put our heads in the sand, not utilizing AI in our business would be a missed opportunity.

It is important to take one step back and ask yourself how you can be more productive and what value proposition AI-based solutions provide you. Ultimately, aiming to delegate repetitive tasks to AI tools is an excellent strategy to ensure that you purely focus on critical workflows where the human factor is inevitable.

About the Author:

Aron Kantor, the editor of TheBusinessDive, is passionate about discussing the latest business trends, startups, and AI advancements.  Aron strives to deliver engaging and valuable content that helps entrepreneurs and future entrepreneurs navigate an ever-changing business landscape.

Der Beitrag 5 Ways How AI Assistants Can Improve Effectiveness erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data Science at Sigli – “How AI-Powered Solutions Can Change the Lives of People with Disabilities”

We’d like to demonstrate that AI can be much more than just another tool that can enhance and streamline a lot of business processes or support companies in reaching an absolutely new level of their productivity. It can also greatly change the lives of many people and make everyday tasks as simple as possible. And from many perspectives, the latter case can be viewed as even more revolutionary than the first one.

Why does it matter?

You may ask us why we believe that this topic deserves so much attention and whether our opinion is based only on the emotional aspect. But we already have an answer that is fully based on the recent statistical data.

The world desperately needs reliable solutions that will help a great part of the population to socialize and live independently (or at least minimize their dependence on assistance from other people). And to fully realize it, it is necessary to have a look at the following figures.

• Around 15% of the population, or estimated 1 billion people, live with disabilities.
• According to the data published by the World Health Organization, as of 2022, at least 2.2 billion people have vision impairment of different severity.
• As for hearing impairment, at the current moment, over 1.5 billion people all over the world are affected by hearing loss in at least one ear. Nearly 13% of adults have hearing difficulty even when using a hearing aid.
• Nearly 20 percent of the world’s population has dyslexia which is the most common of all neuro-cognitive disorders.
• Nearly 1 billion people have a mental disorder.

Let’s admit that these figures look quite impressive. Very often we can’t even imagine how many people suffer from different types of diseases and impairments that make them experience restrictions and limitations even in the simplest everyday processes.

With the development and adoption of AI-powered solutions, every person will have the possibility to live in a world where his or her needs are well-understood and taken into account. And we can’t miss this chance and just ignore the possibilities that are provided to us by artificial intelligence.

Solutions that can fully change the game

To better understand the importance of such solutions you need to think about the inconveniences that people with impairments face every day.

Let’s start with the solutions that are already available to a wide audience, for example, virtual assistants like Siri and Alexa. Without any doubt, people who do not have any health problems also can benefit from using them. But in their case, that’s the question of comfort. Nevertheless, in the case of people with disabilities, it can become a must.

Many of us ask Siri to Google something for us just because we are busy (or lazy). People with visual impairments can do it because they do not want to ask their relatives to find and read something to them. The same principle works even with standard phone functions like calls and messages. Speech recognition, text-to-speech, and speech-to-text features are real game changers. Thanks to virtual assistants, people with partial and complete vision loss can use smartphones (not only button cell phones) as now they can ask AI-powered tools to dial a number or send a message.

But the AI-powered interaction with smartphones is only one of the examples of how artificial intelligence changes the way people can manage and operate various devices. The integration of AI into smart home systems can also brightly demonstrate the power of this technology.

Smart speakers in such systems can become key elements. They can fulfill a lot of tasks based on voice commands (switch on an oven or turn down music), provide recommendations (for example, they can inform when there is enough natural light but all the lamps in the room are still on), and create various scenarios based on the user’s preferences (temperature, lighting, music. etc.). From one perspective, all these features may seem to be redundant. But let’s have a look at them from the perspective of people with limited mobility. It may be difficult for them to go from one room to another in order to check whether their lamps or devices are not consuming too much energy during the day when they do not need them. And AI can do it for them.

Moreover, AI-powered solutions can be enriched with image-recognition functionality. When can it be required at home? When we open a refrigerator, we typically never know where some products are placed and need to start looking for them. But in the case of people with low vision, this task can cause a lot of difficulties. Nevertheless, with a mobile app that will have access to the camera and image-recognition functionality, it will be incomparably easier. A user will need to open this app, point the camera at the shelves, and the app will voice where different products are placed. Similar solutions can also help to read “best before” dates.

Some startups are working even on more advanced devices – AI-powered doorbells enriched with smart cameras. Such devices can “look at” visitors who are standing at the doorbell, recognize them based on the uploaded pictures, and notify users. After getting this information, users can make a decision about whether they want to let such visitors in. Such tech products can greatly enhance the security of people with vision loss, especially of those who live alone.

But now you may ask us whether artificial intelligence can help people only at home. And based on the examples that we’ve mentioned above, the question is absolutely logical. No worries! AI can also greatly increase people’s mobility and boost their integration into society as well.

Already today there are special navigation apps built for users with vision impairments which can fully or partially replace guide dogs. These applications are powered by not only GPS (like standard navigation systems) but also AI tech. Such apps can create routes based on the current traffic, weather, and other conditions and voice detailed instructions for people who can’t read them or use maps on their own. These navigation systems should be much more precise and advanced than traditional apps of this type. They should take into account a lot of external factors in real-time, including possible threats and barriers, and give users highly accurate instructions.

With various apps tailored to the needs of people who have mutism (muteness) or hearing disorders and can’t talk, users can better communicate and share their thoughts with others. They can type their ideas or choose any of the ready-made scripts uploaded to the app, and it will transform the text into speech and voice their ideas instead of them.

Moreover, there are medical cases when hearing aids can’t help people. And here is when a solution that can transform speech into text will be a supportive tool for communication. As a result, people, regardless of their disorders, can feel that they are full-scale participants in any discussion or dialogue.

Conclusion

It’s important to understand that all these examples are only a small part of all possible solutions that can be built for people with disabilities. AI-powered products help them start believing in their forces and their abilities to become a part of society without any restrictions caused by their diseases.

Despite the fact that today there are a lot of talks about artificial intelligence and it may seem that everyone is already aware of the capacities of such solutions, there are still a lot of gaps here. And there is still a lot of work to do for making sure that the potential of AI is clear to society. With the introduction of ChatGPT and all the hype around it, a lot of people have a wrong understanding that such language models can be viewed as the main use case of AI. But such chatbots that can answer your questions, create posts for your Instagram, or compose a plan for an English lesson are only one category of applications that can be powered by artificial intelligence and used in our everyday life.

In reality, AI can offer much more opportunities.

And that’s exactly what we are going to prove in our series of articles devoted to AI-powered solutions for people with disabilities. Stay tuned if you want to know how artificial intelligence can help millions of people to easily cope with a row of tasks that currently may be a real challenge for them.

About the Author:

In his current position, Artem Pochechuev leads a team of talented engineers. Oversees the development and implementation of data-driven solutions for Sigli’s customers. He is passionate about using the latest technologies and techniques in data science to deliver innovative solutions that drive business value. Outside of work, Artem enjoys cooking, ice-skating, playing piano, and spending time with his family.

Der Beitrag How AI-Powered Solutions Can Change the Lives of People with Disabilities erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Dr. Raul V. Rodriguez, Vice President, Woxsen University – “TechnoPsych 2.0: The Evolution of AI and Human Interaction”

Cognitive psychology has played a crucial role in the evolution of artificial intelligence (AI) by providing a better understanding of human cognition and behavior. In recent years, the field has been combined with AI to create a new field called TechnoPsych 2.0, which focuses on designing and developing AI systems that can interact with humans in more natural and intelligent ways. In this article, we will explore the role and importance of cognitive psychology in the development of AI and TechnoPsych 2.0.

Cognitive psychology is the scientific study of mental processes such as perception, attention, memory, language, and problem-solving. It aims to understand how humans process information, make decisions, and interact with their environment. In the field of AI, cognitive psychology has been used to create intelligent systems that can perceive, reason, learn, and communicate like humans.

One of the earliest applications of cognitive psychology in AI was the development of expert systems. Expert systems are computer programs that simulate the decision-making processes of human experts in a particular domain. They use rules and heuristics to analyze data and make decisions based on their knowledge of the domain. For example, an expert system could be developed to diagnose medical conditions based on symptoms reported by a patient.

Cognitive psychology has also been used to develop machine learning algorithms that can learn from data and improve their performance over time. Machine learning algorithms are designed to mimic the learning processes of humans, such as association, generalization, and discrimination. They use statistical methods to identify patterns in data and make predictions based on those patterns. For example, machine learning algorithms could be used to analyze customer data and predict which products they are most likely to buy.

More recently, cognitive psychology has been combined with natural language processing to create conversational agents or chatbots. These AI systems are designed to interact with humans in a natural language and provide assistance, guidance, or entertainment. They use speech recognition, natural language understanding, and natural language generation to understand and generate human language. For example, chatbots could be used to provide customer service or answer questions about a product.

The integration of cognitive psychology and AI has led to the development of TechnoPsych 2.0, which aims to create AI systems that can interact with humans in more natural and intelligent ways. TechnoPsych 2.0 focuses on designing AI systems that can perceive human emotions, understand human intentions, and respond appropriately to human needs. This requires a deeper understanding of human psychology and behavior.

For example, TechnoPsych 2.0 could be used to develop AI systems that can recognize and respond to human emotions. Emotion recognition is a complex task that involves the analysis of facial expressions, body language, tone of voice, and other nonverbal cues. AI systems that can recognize emotions could be used to provide emotional support to people suffering from depression or anxiety.

TechnoPsych 2.0 could also be used to develop AI systems that can understand human intentions and respond appropriately. This requires a deeper understanding of human language and context. For example, AI systems could be developed to understand and respond to sarcasm or irony in human language.

In conclusion, cognitive psychology has played a crucial role in the evolution of AI by providing a better understanding of human cognition and behavior. The integration of cognitive psychology and AI has led to the development of TechnoPsych 2.0, which aims to create AI systems that can interact with humans in more natural and intelligent ways. As AI technology continues to advance, TechnoPsych 2.0 will play an increasingly important role in creating AI systems that can understand and respond to human needs.

About the Author:

Dr. Raul Villamarin Rodriguez is the Vice President of Woxsen University. He is an Adjunct Professor at Universidad del Externado, Colombia, a member of the International Advisory Board at IBS Ranepa, Russian Federation, and a member of the IAB, University of Pécs Faculty of Business and Economics. He is also a member of the Advisory Board at PUCPR, Brazil, Johannesburg Business School, SA, and Milpark Business School, South Africa, along with PetThinQ Inc, Upmore Global and SpaceBasic, Inc. His specific areas of expertise and interest are Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotic Process Automation, Multi-agent Systems, Knowledge Engineering, and Quantum Artificial Intelligence.

Der Beitrag TechnoPsych 2.0: The Evolution of AI and Human Interaction erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.