SwissCognitive Guest Blogger: Zachary Amos – “How Countries Are Using AI to Predict Crime”

A world where police departments can predict when, where and how crimes will occur seems like something from a science fiction novel. Thanks to artificial intelligence, it has become a reality. Already, countries are using this technology to forecast misconduct.

How Do AI-Powered Crime Prediction Systems Work?

Unlike regular prediction systems — which typically use hot spots to determine where and when future misconduct will be committed — AI can analyze information in real time. It may even be able to complete supplementary tasks like summarizing a 911 call, assigning a severity level to a crime in progress or using surveillance systems to tell where wanted criminals will be.

A machine learning model evolves as it processes new information. Initially, it might train to find hidden patterns in arrest records, police reports, criminal complaints or 911 calls. It may analyze the perpetrator’s demographic data or factor in the weather. The goal is to identify any common variable that humans are overlooking.

Whether the algorithm monitors surveillance camera footage or pours through arrest records, it compares historical and current data to make forecasts. For example, it may consider a person suspicious if they cover their face and wear baggy clothes on a warm night in a dark neighborhood because previous arrests match that profile.

Countries Are Developing AI Tools to Predict Crime

While these countries don’t currently have official AI prediction tools, various research groups and private police forces are developing solutions.

• United States

Violent and property crimes are huge issues in the United States. For reference, a burglary occurs every 13 seconds — almost five times per minute — causing an average of $2,200 in losses. Various state and local governments are experimenting with AI to minimize events like these.

One such machine learning model developed by data scientists from the University of Chicago uses publicly available information to produce output. It can forecast crime with approximately 90% accuracy up to one week in advance.

While the data came from eight major U.S. cities, it centered around Chicago. Unlike similar tools, this AI model didn’t depict misdemeanors and felonies as hot spots on a flat map. Instead, it considered cities’ complex layouts and social environments, including bus lines, street lights and walkways. It found hidden patterns using these previously overlooked factors.

• South Africa

Human trafficking is a massive problem in South Africa. For a time, one anti-human trafficking non-governmental organization was operating at one of the country’s busiest airports. After the group uncovered widespread corruption, their security clearance was revoked.

At this point, the group needed to lower its costs from $300 per intercept to $50 to align with funding and continue their efforts. Its members believed adopting AI would allow them to do that. With the right data, they could save more victims while keeping costs down.

Some Are Already Using AI Tools to Predict Crime

Governments have much more power, funding and data than nongovernmental organizations or research groups, so their solutions are more comprehensive.

• Japan

Japan has an AI-powered app called Crime Nabi. The tool — created by the startup Singular Perturbations Inc. — is at least 50% more effective than conventional methods. Local governments will use it for preventive patrols.

Once a police officer enters their destination in the app, it provides an efficient route that takes them through high-crime areas nearby. The system can update if they get directed elsewhere by emergency dispatch. By increasing their presence in dangerous neighborhoods, police officers actively discourage wrongdoing. Each patrol’s data is saved to improve future predictions.

Despite using massive amounts of demographic, location, weather and arrest data — which would normally be expensive and incredibly time-consuming — Crime Nabi processes faster than conventional computers at a lower cost.

• Argentina

Argentina’s Ministry of Security recently announced the Artificial Intelligence Applied to Security Unit, which will use a machine learning model to make forecasts. It will analyze historical data, scan social media, deploy facial recognition technology and process surveillance footage.

This AI-powered unit aims to catch wanted persons and identify suspicious activity. It will help streamline prevention and detection to accelerate investigation and prosecution. The Ministry of Security seeks to enable a faster and more precise police response.

• South Korea

A Korean research team from the Electronics and Telecommunications Research Institute developed an AI they call Dejaview. It analyzes closed-circuit television (CCTV) footage in real time and assesses statistics to detect signs of potential offenses.

Dejaview was designed for surveillance — algorithms can process enormous amounts of data extremely quickly, so this is a common use case. Now, its main job is to measure risk factors to forecast illegal activity.

The researchers will work with Korean police forces and local governments to tailor Dejaview for specific use cases or affected areas. It will mainly be integrated into CCTV systems to detect suspicious activity.

Is Using AI to Stop Crime Before It Occurs a Good Idea?

So-called predictive policing has its challenges. Critics like the National Association for the Advancement of Colored People argue it could increase racial biases in law enforcement, disproportionately affecting Black communities.

That said, using AI to uncover hidden patterns in arrest and police response records could reveal bias. Policy-makers could use these insights to address the root cause of systemic prejudice, ensuring fairness in the future.

Either way, there are still significant, unaddressed concerns about privacy. Various activists and human rights organizations say having a government-funded AI scan social media and monitor security cameras infringes on freedom.

What happens if this technology falls into the wrong hands? Will a corrupt leader use it to go after their political rivals or journalists who write unfavorable articles about them? Could a hacker sell petabytes of confidential crime data on the dark web?

Will More Countries Adopt These Predictive Solutions?

More countries will likely soon develop AI-powered prediction tools. The cat is out of the bag, so to speak. Whether they create apps exclusively for police officers or integrate a machine learning model into surveillance systems, this technology is here to stay and will likely continue to evolve.

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 Countries Are Using AI to Predict Crime erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: theconversation.com – “AI and Criminal Justice: How AI Can Support – Not Undermine – Justice”

Interpol Secretary General Jürgen Stock recently warned that artificial intelligence (AI) is facilitating crime on an “industrial scale” using deepfakes, voice simulation and phony documents.

Police around the world are also turning to AI tools such as facial recognition, automated licence plate readers, gunshot detection systems, social media analysis and even police robots. AI use by lawyers is similarly “skyrocketing” as judges adopt new guidelines for using AI.

While AI promises to transform criminal justice by increasing operational efficiency and improving public safety, it also comes with risks related to privacy, accountability, fairness and human rights.

Concerns about AI bias and discrimination are well documented. Without safeguards, AI risks undermining the very principles of truth, fairness, and accountability that our justice system depends on.

In a recent report from the University of British Columbia’s School of Law, Artificial Intelligence & Criminal Justice: A Primer, we highlighted the myriad ways AI is already impacting people in the criminal justice system. Here are a few examples that reveal the significance of this evolving phenomenon.

The promises and perils of police using AI

In 2020, an investigation by The New York Times exposed the sweeping reach of Clearview AI, an American company that had built a facial recognition database using more than three billion images scraped from the internet, including social media, without users’ consent.

Policing agencies worldwide that used the program, including several in Canada, faced public backlash. Regulators in multiple countries found the company had violated privacy laws. It was asked to cease operations in Canada.

Clearview AI continues to operate, citing success stories of helping to exonerate a wrongfully convicted person by identifying a witness at a crime scene; identifying someone who exploited a child, which led to their rescue; and even detecting potential Russian soldiers seeking to infiltrate Ukrainian checkpoints.[…]

Read more: www.theconversation.com

Der Beitrag AI and Criminal Justice: How AI Can Support – Not Undermine – Justice erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Zachary Amos – “How AI-Powered Drones Could Fight Wildfires”

With climate change driving hotter, drier conditions, wildfire prevention has become more urgent than ever. Wildfires destroy ecosystems, endanger lives and release massive carbon emissions that worsen global warming. Autonomous drones with AI emerge as an innovative tool to tackle this threat by offering early detection and rapid response capabilities.

High-tech sensors and real-time data allow AI-driven devices to scan expansive, hard-to-reach landscapes. They can spot smoke signals early, analyze environmental risk factors and predict areas most vulnerable to fires. This innovative approach empowers authorities and communities with faster, more accurate prevention tools that promise safer outcomes for people.

Early Smoke Detection

AI-powered drones address a critical weakness in traditional smoke surveillance methods. Conventional practices often struggle with low accuracy and miss early signs of smoke that is transparent or without clear edges. In contrast, these intelligent tools monitor vast, hard-to-reach landscapes. They use advanced sensors to track air quality and temperature shifts that can indicate a fire’s first stages.

Unlike human surveillance — which has limited reach — AI-driven drones identify subtle anomalies in smoke patterns and pinpoint potential fire locations that might otherwise go unnoticed. With real-time data transmission, these devices alert authorities and enable a rapid response to contain fires before they escalate.

Identifying High-Risk Areas

AI drones analyze critical factors like vegetation density, moisture levels and drought conditions to identify higher-risk areas. They use advanced sensors to collect detailed environmental data and flag locations where dense, dry vegetation and prolonged drought create ideal fire conditions.

This insight helps forest services craft smarter prevention strategies, from clearing overgrown brush to focusing monitoring efforts where it matters most. Moreover, these drones improve risk analysis over time with machine learning algorithms that continuously adapt to seasonal and environmental shifts. This approach to data analytics allows organizations to make well-informed decisions and strategically deploy resources to protect vulnerable landscapes.

Monitoring Lightning Strikes

Drones track lightning strike patterns and focus on recently hit areas. This is a crucial approach since lightning remains one of the top causes of wildfires across the 3 trillion trees on Earth. They can spot even the smallest flare-ups with infrared sensors — regardless of harsh weather conditions — which helps them from growing into uncontrollable blazes.

Acting quickly after a lightning strike is essential, and drones make that possible by instantly sending alerts to fire teams when they detect heat anomalies. Authorities can use this technology to respond swiftly and safeguard forests and communities from the devastating impact of wildfires.

Delivering Fire Suppression Supplies

Drones can autonomously deliver fire retardants, water, and other supplies to remote areas that are challenging or dangerous for ground crews to access. These devices use AI algorithms to analyze fire spread patterns, wind conditions and terrain to make precise, targeted drops where they’re most effective.

This capability mirrors the e-commerce industry’s success, where drones completed over 660,000 delivery flights between 2019 and 2022, showcasing the reliability of this transport method in real-world scenarios. Reaching early-stage fires swiftly and efficiently allows these devices to tackle potential wildfire threats before they escalate. They offer a proactive approach that protects natural areas and nearby communities.

Mapping Safe Evacuation Areas

Drones with AI create updated evacuation maps based on real-time analysis of fire spread. This tool is essential in protecting the over 115 million people in the U.S. living in high-risk wildfire counties. Predicting fire movement patterns helps drones pinpoint areas in imminent danger and alert communities. It ensures evacuations are timely and directed toward the safest routes.

These dynamic, drone-generated maps offer critical support to first responders and residents because they adapt to shifting fire lines and environmental changes. Access to accurate, real-time evacuation maps can be lifesaving for those in wildfire-prone areas. They guide residents away from harm’s path with clear, updated information.

Expanding AI-Driven Solutions for a Safer Environment

The potential for integrating AI-driven drones into wildfire prevention strategies is vast. They offer powerful tools to protect ecosystems and safeguard communities at risk. Staying informed about AI and autonomous technology advancements opens doors to supporting and participating in the next wave of environmental protection innovations.

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-Powered Drones Could Fight Wildfires erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: htworld.co.uk – “The EU’s Artificial Intelligence (AI) Act: The First Of Its Kind”

The EU has introduced new legislation on AI, the EU AI Act, which lays the foundation for the regulation of, and responsible development of, AI across all industries within the EU.

The Act was published in the Official Journal of the EU on 13 July 2024 and is due to enter into force on 2 August 2024.

While it will be the first of its kind to come into effect globally, it seems Colorado in the US is not far behind, being the first US state to recently pass comprehensive legislation on the issue.

This article will look at what the EU AI Act says, how it categorises AI systems, what is prohibited under the Act and what is deemed high risk.

While the Act will be relevant to many industries, this article will briefly consider some of the implications for Medtech specifically and will also touch on how the Act compares with Colorado’s equivalent.

What the EU AI Act says

How the Act categorises AI systems?

The Act classifies AI according to its risk:

• Unacceptable risk: Unacceptable risk is prohibited (e.g. manipulative AI and social scoring systems);
• High risk: Most of the Act addresses high risk AI systems, which are regulated;
• Limited risk: A smaller section of the Act addresses limited risk AI systems, which will be subject to lighter transparency requirements (e.g. developers/deployers must ensure that end-users are aware they are interacting with AI); and
• Minimal risk: Minimal risk is unregulated (includes various AI applications such as video games and spam filters)

What systems are prohibited?

According to the Act (quoting https://artificialintelligenceact.eu/high-level-summary/), the following types of Artificial Intelligence systems are prohibited, those:

• deploying subliminal, manipulative, or deceptive techniques to distort behaviour and impair informed decision-making, causing significant harm.
• exploiting vulnerabilities related to age, disability, or socio-economic circumstances to distort behaviour, causing significant harm.
• biometric categorisation systems inferring sensitive attributes (race, political opinions, trade union membership, religious or philosophical beliefs, sex life, or sexual orientation), except labelling or filtering of lawfully acquired biometric datasets or when law enforcement categorises biometric data.
• social scoring, i.e., evaluating or classifying individuals or groups based on social behaviour or personal traits, causing detrimental or unfavourable treatment of those people.[…]

Read more: www.htworld.co.uk

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Copyright: forbes.com – “What Every CEO Needs To Know About The New AI Act”

Potentially dangerous AI applications have been designated “unacceptable” and will be illegal except for government, law enforcement, and scientific study under specific conditions.

As was true with GDPR, this new EU legislation will create new obligations for anyone who does business within the 27 member states, not just the companies based there.

Those responsible for writing it have said that the aim is to protect citizens’ rights and freedoms while also fostering innovation and entrepreneurship. But the 460-odd published pages of the Act contain a lot more than that.

If you run a business that operates in Europe or sells to European consumers, though, there are some important things you need to know. Here are what stands out to me as the key takeaways for anyone who wants to be prepared for potentially significant changes.

When Does It Come Into Force?

The Artificial Intelligence Act was adopted by the EU Parliament on March 13 and is expected to soon become law when it is passed by the European Council. It will take up to 24 months for all of it to be enforced, but enforcement of certain aspects, such as the newly banned practices, could start to happen in as little as six months.

As was the case with GDPR, this delay is to let companies ensure they’re compliant. After this deadline, they could face significant penalties for any breaches. These are tiered, with the most serious reserved for those breaking the “unacceptable uses” ban. At the top end are fines of up to 30 million euros, or six percent of the company’s global turnover (whichever is higher!)

Potentially even more damaging, though, would be the impact on a business’s reputation if it’s found to be breaking the new laws. Trust is everything in the world of AI, and businesses that show they can’t be trusted are likely to be further punished by consumers.[…]

Read more: www.forbes.com

Der Beitrag What Every CEO Needs To Know About The New AI Act erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

For the conference details, agenda, speaker line-up, and handouts CLICK HERE.
For the conference recording CLICK HERE
“The AI Trajectory 2024. Invest for Impact Wrap-up”

Yesterday, at the “AI Trajectory 2024 – Invest for Impact” virtual conference, we embarked on an enlightening journey, exploring the multifaceted role of AI across various sectors. From dissecting investment strategies in AI to leveraging its potential in healthcare, the event unfolded as a tapestry of insights, innovations, and forward-thinking discussions. Esteemed speakers from diverse industries shared their profound expertise, shedding light on the transformative impact of AI and setting the stage for a future where technology and humanity coalesce more seamlessly than ever. This article serves as a wrap-up for those who missed this illuminating event, encapsulating the key highlights and takeaways from our panel of visionary experts.

Why Invest in AI Today

With Petra Vorsteher and Ragnar Kruse.

We stand at the threshold of a transformative era, where AI’s role in our lives is not just supportive but deeply integral. Investing in AI today is not just an option but a necessity, propelled by its rapid technological maturity and the increasing attention it commands at the top echelons of business leadership.

Dalith Steiger, Co-Founder of SwissCognitive, World-Leading AI Network, Petra Vorsteher, Founding Partner AI.FUND; Founding Partner AI.INVEST, Ragnar Kruse, Founding Partner & Managing Director, AI.FUND; Founder, AI.HAMBURG

The Future of Investments in AI Foundation Models

With Jacques Ludik, Cinderella Amar, David Shrier, Nils Reimers, John Wesley

The discussion around AI foundation models marked a pivotal shift in perspective. It’s a landscape where democratization of technology grapples with security and ethical use. For investors, grasping these nuances is vital for safeguarding their interests and remaining ahead in a rapidly changing environment. This includes striking a balance between harnessing proprietary data and adapting to the trend of democratization. They must navigate a world where foundational AI models, once the domain of a select few due to high development costs, are now becoming more accessible, prompting a need for innovative and sustainable business models.

Jacques Ludik, Founder & CEO, Cortex Logic & Cortex Group, Founder & President, Machine Intelligence Institute of Africa, Cinderella Amar, Managing Partner, Glass Ventures, David Shrier, Professor of Practice, AI & Innovation, Imperial College Business School; Founder & Managing Director, Visionary Future, Nils Reimers, Director of Machine Learning, Cohere, John Wesley, Senior Investment Director, NVentures

Bringing the Reading Gap: AI Innovations in Dyslexia Support

With Artem Pochechuev

The landscape of technology is undergoing a profound transformation with AI-driven initiatives, significantly impacting both education and practical applications. In the realm of education and personal development, AI is revolutionizing the way we support individuals with dyslexia, serving as a prime example of how human-centric AI systems are unlocking people’s full potential.

Artem Pochechuev, AI Expert, Head of Data Science, Sigli

Healthcare Industry Transformation – Harnessing Automation, AI, and Talent

With Alexander Büsser, Laura Modiano, Anita Puppe, Heinrich Zetlmayer, Jose Pedro Almeida

The integration of generative AI in healthcare is creating a paradigm shift by efficiently structuring and analyzing complex data, leading to improved patient care and outcomes. This technology is crucial in consolidating fragmented data, transforming workflows, and the healthcare value chain, thereby enhancing efficiency and freeing resources for more critical tasks. Looking to the future, AI is pivotal in addressing global healthcare challenges, facilitating international collaboration and the sharing of medical data, and fostering a more unified and effective global healthcare system.

Alexander Büsser, Director Data, AI & Platforms, Idorsia Pharmaceuticals, Laura Modiano, Principal Venture Capital and Startups Business Development, EMEA AWS, Anita Puppe, Healthcare Industry AI Transformation Leader; Senior Consultant Strategy & Business Design, IBM iX DACH, Heinrich Zetlmayer, General Partner, yabeo; Founder & General Partner, Blockchain Valley Ventures, Jose Pedro Almeida, Chief AI Strategist for Healthcare, Advisory Board Member, Intelligence Ventures

Computer Vision in Water

With Omer Bar-Ilan, Co-Founder, CEO, Lynxight

Simultaneously, the integration of computer vision in aquatic environments marks the dawn of a new technological era. This technology is not only optimizing feeding patterns and enhancing navigation for underwater ROVs but also playing a critical role in public safety. Its capability to rapidly assess risks in water environments, such as swimming pools, for drowning prevention, is a testament to its versatility and impact, showcasing the diverse and transformative applications of AI across various sectors.

Omer Bar-Ilan, Co-Founder, CEO, Lynxight

STEM Evolution 2024: Redefining Science in the Age of AI and LLM

With Solomon Amar, Jeanne Lim, Stéphanie Bretonniere, Arnaud Quintin, Assaf Araki

In the evolving landscape of STEM, we are witnessing a redefinition of scientific approaches and applications. This includes the development of scalable science-based applications that leverage content generation, idea ideation, and knowledge navigation, all underpinned by engaging AI bots. In In the meantime, AI’s role in industries like food and automotive is transformative, optimizing resources like water for sustainability and reshaping customer engagement and internal processes. Of course, this progress is accompanied by challenges in privacy, bias, and the need for regulatory measures, highlighting the importance of a balanced and ethical approach to AI integration in our society.

Solomon Amar, Founder & CEO, ALLSTARSIT; Founder, AI Labs, Jeanne Lim, Angel Investor, Co-founder & CEO, beingAI, Stéphanie Bretonniere, Founder & CEO, WE IMPACT.WORLD, Arnaud Quintin, VP, Organisation and Transformation, Renault Group, Assaf Araki, Investment Director, Intel Capital

Rhythmic Intelligence: AI’s Impact on Music and Health

With Walter Werzowa

Finally, we head how AI is revolutionizing the music industry by enabling anyone to create music, thereby enhancing creativity and democratizing the art form. Rather than feeling threatened, we can learn more about how currently available technology and AI can help us take our music-making skills to even higher levels creating works that were previously impossible.

Walter Werzowa, University Professor – University of Music and Performing Arts Vienna; Head Of Music, MYTHOS MOZART

If you missed our “The AI Trajectory 2024. Invest for Impact.” virtual conference, here you can find the video recording:

For the conference details, agenda, speaker line-up and handouts CLICK HERE

Der Beitrag Navigating the Future: The AI Trajectory 2024 – Invest for Impact Virtual Conference Wrap-up erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Artem Pochechuev, Head of Data Science at Sigli – “How AI-powered tools can help people with hearing impairments”

According to the data provided by the WHO, by 2050, 1 in every 10 people, or in total over 700 million, will suffer from disabling hearing loss. And it is a very impressive figure. While some people lose hearing abilities in life span, others are born with hearing impairments and have no other choice but to use sign language for communication.

Hearing loss and deafness often influence such aspects of people’s lives as cognition, education, and employment, which can result in loneliness and full social isolation. The history of electronic hearing aids started more than a century ago, in 1898 practically just after the introduction of the telephone by Alexander Graham Bell in 1876. However, we can’t say that today they can fully solve the problems of people with hearing impairments. Even modern hearing aids are far from being perfect, they have a lot of limitations and may cause a lot of discomfort for their users.

Nevertheless, thanks to emerging technologies (and Artificial Intelligence occupies a leading position among them), we can change our approach to making our environment better for people with partial or full hearing loss.

In this article, we offer you to have a look at the new opportunities that AI opens to us in addressing the difficulties that people with hearing impairments face every day.

AI tools: Use cases and examples

To begin with, we should mention that today hearing aid manufacturers have already started demonstrating their interest in the capabilities of AI and are studying the possibility of making their devices more advanced with it. We should admit that such AI-powered hearing aids have a high chance of becoming game-changers.

Usually, digital hearing aids have so-called modes or programs, like a TV mode or a home program. These modes include static settings that correspond to different environments. However, such settings can be okay in very standardized conditions only and they won’t match up to unique circumstances. AI used in hearing systems works another way. It does not rely on strictly set modes but is able to adjust them in real-time based on the experiences of a user.

For example, when a user is visiting a crowded place with his or her spouse, AI-powered hearing aids that are enriched with noise-cancellation technologies can make their communication much more comfortable than it used to be without such tools. This device will be able to define the voice that a user hears most often and prioritize it over all others around while canceling other noises and sounds.

Cutting-edge hearing aids may also have sound amplification tools. In other words, when somebody is speaking too quietly or, for example, through a mask that obviously mutes sounds, AI-powered devices can detect such issues and amplify the sound in real time.

All this may seem too futuristic but such devices already exist. One of them is Widex Moment Sheer which was introduced in September 2022. Widex is focused on the quality of sound and utilizes AI and ML for designing hearing modes based on users’ typical environments.

But are AI-powered hearing aids the only options for helping people with hearing impairments? And what can be offered to people with full hearing loss? It’s high time to speak about solutions of other types.

A lot of people with hearing impairments have a well-developed skill of lip reading which means that they can understand what others say by interpreting the movements of their faces, lips, and tongues. This skill is highly valuable for them but the problem is that due to various kinds of disabilities, including muteness, they can’t use natural speech and use sign language to express their thoughts. It can become a barrier to synchronous communication when their partners do not know how to interpret all signs and gestures. Moreover, how is it possible to organize communication if a person is not good at lip reading or if it is not possible to interpret lip movements amid the ongoing conditions? Here’s when we should mention the possibility of building AI-powered sign language translators.

AI-powered Kinect Sign Language Translator by Microsoft is a solution that can convert signs into a spoken or written language and, vice versa, it can convert natural language into signs. To use such a tool, it is necessary to have a computer and a Kinect camera that will recognize gestures and provide their translation in real time. A similar process takes place when a hearing person is speaking. The system is “listening” to the speech and then transforms the words into signs.

But Microsoft is not the only company that is standing behind a sign language translator. A lot of startups are also working on similar solutions. In 2018, a Netherlands-based startup GnoSys introduced its app that is intended for translating sign language into speech and written text in real time. The application relies on neural networks and computer vision for recognizing sign language. Then with the help of smart algorithms, the recognized signals are transformed into speech.

The above-mentioned tools can help a lot in face-to-face communication which is highly important for the socialization of people and their possibility of getting a job. However, in our article, we also need to mention solutions that will revolutionize the online experience for people with deafness or other hearing impairments. How do these people usually watch films? With captions. But what can be done if there are no added captions? AI real-time captioning and transcription services can address this issue. And what is more important, such services will be of great use not only for movie lovers, they can be applied during lifestreaming, Zoom meetings, online lessons, etc. It’s will a great idea to rely on real-time captioning tools if you organize online events for a wide audience to ensure better inclusivity.

Verbit is one of the vendors that provides such services. What makes the offered tools extremely comfortable is the possibility to integrate them directly into streaming or conferencing platforms like YouTube, Twitch, or Zoom for seamless experiences. Such services are also popular among those who are watching videos in a non-native language or those who can’t use their headphones. However, the community of people with hearing loss can benefit from them most of all as for them the use of real-time captioning is not just a question of comfort but also a must.

It’s also crucial to mention that AI can also contribute to increasing safety for people with hearing loss which can affect their ability to react to emergencies. For example, let’s consider driving. Hearing impairments do not have a direct impact on driving skills but due to them, people can’t hear important sounds like sirens of emergency vehicles. These sirens always indicate a necessity to quickly react and make way for such vehicles as fire trucks or ambulances. When a driver doesn’t hear these sounds, he or she can’t take any measures which can lead to dangerous road situations. Engineer Jan Říha paid attention to these risks and developed a smart device dubbed PionEar. It relies on an audio classification algorithm and is able to analyze background noise and recognize the sounds of emergency vehicles. When such sounds are detected, a driver will be alerted with the help of a visual cue.

However, sometimes, to make our society more suitable for everyone, we do not need to create something exclusive for a particular community. Sometimes it will be enough to adapt something that was created for wide circles to the needs of some groups.

Virtual assistants with text-to-speech and speech-to-text capabilities like Siri are among such examples. If a girl with hearing impairments needs to make an appointment at a beauty salon, what options does she have? She can write a message. But what if administrators don’t have time to read messages? She can ask her friend or sister to do it. But it’s not always possible. Moreover, it will require additional time and effort. With a virtual assistant, everything will be easier. It will be enough to activate Siri by using a voice command or the Type to Siri mode and ask it to make a call to a beauty salon.

Yes, at the moment, this functionality still requires enhancements. But we are here to make the world a better place to live for everyone by means of technology. Right?

Closing word

The range of AI use cases that we’ve considered in this blog post is a cool demonstration of how modern tech solutions can help us break down the barriers that used to exist (and are still existing) for people with any type of disability, not only hearing impairments. Thanks to modern AI-powered tools, people will have the possibility to be fully integrated into society. And what is probably even more important, our society will become more inclusive for them.

In the series of our blog posts, we will continue talking about the ways AI can help us to reach such goals. 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 How AI-Powered Tools Can Help People With Hearing Impairments erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: forbes.com – “Artificial Intelligence And The Boardroom: Immediate Actions Items”

It is still relatively early days, and for many, AI is simply customer service Chatbots, and self-driving car features. Or ChatGPT and the endlessly entertaining opportunity to ask all types of random questions, much as we did when Alexa showed up some years ago.

But for business leaders, AI is an unstoppable game-changer. It is the ability to improve productivity and performance, discover new products and services, and improve business results in many unanticipated ways. “McKinsey recently reported that “Generative AI’s impact on productivity could add trillions of dollars in value to the global economy.” McKinsey’s 2023 “research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases we analyzed—by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion.”¹ Truly staggering!

The potential of AI and its impact is increasing daily and exponentially. Companies of all shapes, sizes, and stages have an opportunity to take advantage of the revolution or risk getting left behind. The Board of Directors, as the ultimate governing body of the organization, must be focused on this now. Here are four ways to begin:

Understanding AI

As the old Chinese proverb states, “A journey of a thousand miles begins with a single step.” And, of course, to leverage the momentousness of AI, we must first understand it. This does not necessarily mean full-blown technical expertise in the boardroom – although this can help in certain circumstances. Instead, it means that everyone on your board should have a firm grasp of what AI is, the different types of AI, and a sense of what AI is changing in your particular industry or amongst your clients and suppliers. Additionally, this should not be left to chance, individual dabbling, or casual reading on the topic. The board should put AI knowledge and education on its agenda.[…]

Read more: www.forbes.com

Der Beitrag Artificial Intelligence And The Boardroom: Immediate Actions Items erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Gregg Barrett, Chief Executive Officer, Cirrus – “A Sound of Hope for South Africa in the Fight Against Trafficking with AI”

The release of the movie, the Sound of Freedom, while not representative of all the facets of current day human trafficking, has helped initiate broader conversations about modern exploitation. For many who watch the movie the feeling will be that doing something is better than doing nothing. But what can be done that will actually help? I was presented with this question in 2021 by an anti-human trafficking (AHT) NGO operating in South Africa and internationally. Prior, the organisation had been operating at one of South Africa’s busiest airports, and in the course of their work had uncovered systemic corruption and organised crime involved in trafficking at the airport. As a result, their security clearance had been revoked preventing them from operating in the airport. Their cost per intercept was around 300 USD which needed to be reduced to around 50 USD to align with funding. Astutely they believed that turning to the adoption of artificial intelligence (AI) methods would allow them to increase the efficiency and effectiveness of their work, and that this could be scaled without a resulting scaling in cost and headcount. Could there be a greater application of AI than that which results in the saving of lives? [1]

From an institutional governance standpoint, South Africa’s law enforcement institutions are not resourced to the same extent as many of those in the developed western world. [2] Under such conditions trafficking thrives, elevating the role of civil society organisations. However, as with law enforcement, these civil society organisations are not equipped with the optimal tools to enable the application of AI in the fight against trafficking. In understanding the scope and nature of human trafficking in South Africa, the United States Agency for International Development released a first report from a larger authoritative study. Five key points from the report are instructive:

• Human trafficking is indeed a serious, pervasive, and systemic problem in South Africa, that seamlessly intersperses with other crimes and social phenomena — including gender-based violence, prostitution, organised crime, missing persons, irregular migration, child abuse and labour disputes, to name a few.
• South Africa is not nearly equipped or co-ordinated enough to deal with this crime as effectively as it should or could, and enabling factors such as corruption, complicity, and compromise of officials and other AHT role players is a constant stark background to AHT efforts.
• There is poor record keeping, inaccessibility of official trafficking data, and the absence of an integrated information system required to collate and analyse specific information.
• A lack of proactive investigations and intelligence sharing, and a largely inactive national AHT task team, means that evidence of South Africa as a transit country is not proactively pursued with international counterparts.
• Citing a 2019 multi-country report by the UN, the report says South Africa is a “main destination” for smuggled and trafficked persons on the African continent. According to that 2019 report: “Most Africans see South Africa as the easiest country of transit to reach Europe or the Americas”, and it is “an origin and transit country for trafficking towards Europe and North America, and for trafficking and smuggling to and from Latin America and Asia”.

Returning to 2021 in my engagements with the NGO, the first step became obvious. We needed to focus on the data. Data is the necessary input for the training of AI models and their deployment (inference). In North America for example, Polaris operates the U.S. National Human Trafficking Hotline. Through that work, they have built the largest known dataset on human trafficking in North America, with the data informing real time strategies. Underpinning Polaris is what is known as a data management platform. It is this nontrivial piece of technology that effectively enables the application of AI to AHT.

At a high level a data management platform provides the capability needed to store, manage, share, find and use data for AI. A database is not a data management platform. Rather a data management platform is required for a single point of data ingestion. As the name implies this is to ingest data in all its forms (structured, unstructured, and semi-structured), and with all key data transfer approaches (batch, micro-batch, and streaming). To do this the data management platform provides a highly configurable set of data integration tools that extend far beyond typical extract-transform-load (ETL) or extract-load-transform (ELT) solutions.

In the context of AHT the data management platform provides the operational fabric that enables the access control framework to restrict access to sensitive information at a granular level, ensuring that analysts see only the specific data points that are necessary to complete their work. This ensures that data is being used effectively to have a positive impact, while protecting the privacy of individuals. The platform also enables detailed privacy impact assessments to codify the risks of the data used and the development of mitigation plans.

Beyond this the existence of a data management platform more fully enables the utilisation of mobility data, a financial intelligence unit, a research hub, and philanthropic engineering support. Mobility data is needed to generate heatmaps to identify choke points for placing new stations with human monitors to intercept trafficked persons. The financial intelligence units’ purpose is to train financial services and anti-money laundering staff on the data management platform itself, and allows these professionals to share knowledge, information, and best practices in real-time. In addition, this unit is intended to help survivors of human trafficking get access to banking services that they would not otherwise qualify for because of poor credit and other issues related to their trafficking experience. The research hub is there to bolster the data science / AI capabilities of the AHT organisations by establishing collaborations with academia and industry. This includes a data facility to provide key data to researchers, academics, law enforcement officers and others seeking to deepen knowledge and understanding in the fight against trafficking. Lastly, philanthropic engineering support is intimately connected to a commercial operation, and develops deep, hands-on, and often long-term relationships with NGOs and social sector organisations. This includes on-site engineering to develop foundational understanding of the respective fields enabling the establishment of broader collaborations of players to work on solving social problems. In the context of AHT, philanthropic engineering support provides the capability to drive on-the-ground action with partners that: have the capacity to utilise data management and AI for maximum impact; with organisations that have data and develop data sources; will benefit from AI analysis of the data; and have staff in place to act on the insights to drive action. Importantly, while philanthropic engineering support directly improves and save lives, the engagements also have a powerful impact internally, helping to attract, retain, and engage employees. The challenges being tackled require world class engineers and in South Africa there is a dire need to create opportunities to cultivate this talent – to offer meaningful work and the chance to make a difference.

Yet, here in South Africa a Polaris like data management platform has not been in sight. Enter anti-money laundering (AML). As with human trafficking, South Africa is plagued by money laundering. In February the country was greylisted by global financial crime watchdog the Financial Action Task Force (FATF) for not fully complying with international standards around the prevention of money laundering, terrorist financing and proliferation financing. Presently, each bank in South Africa undertakes AML mostly in isolation. A recent Bank for International Settlements project confirmed that collaborative analysis and learning approaches were more effective in detecting money laundering networks than the current siloed approach in which financial institutions carry out analysis in isolation. By the numbers, a LexisNexis report found South Africa’s largest banks spent on average 12.3 million USD in financial crime compliance operations in 2021. Further, the total projected cost of financial crime compliance in South Africa increased by 65% between 2019 and 2021, from $2.3 billion USD to $3.8 billion USD.

Contrasting deficiencies in human trafficking and money laundering show significant overlaps. This is unsurprising given that both fundamentally involve intelligence gathering, requiring the very same technological toolsets. Unquestionably, AI is the future for AML and AHT, and South Africa requires an industry wide approach – an industry wide data management platform. Just such an intervention has been initiated, where the intention is that the data management platform and its related operations for AML will be placed into a shared entity co-owned by industry. There is precedent for such. The country’s banks collaborate and co-own Bankserv, the automated clearing house. For South Africa’s largest banks an industry wide AML platform will result in significantly enhanced AML capabilities and cost reductions to around one third of their current financial crime compliance spend. For the country, eventual removal from the FATF greylisting. And for South Africa’s AHT organisations, the provision of a world class platform enabling the application of AI to fight trafficking.

In summary, out of South Africa’s struggles arises an opportunity for the country to be a global leader in the fight against trafficking and money laundering. Technological interventions like this do not come to pass by chance but through leadership. For what is it if we have these technological capabilities but fail to implement? Do we not have an ethical obligation? We must be pragmatic and assume that based on experience Government leadership is unlikely to materialise, and be optimistic that there are leaders in industry with the vision and fortitude to pursue this endeavour that will ultimately save lives. That there are those who are motivated in their hearts and minds to actually do something that will make a difference.

[1]

Ways in which long-range research in AI could be applied to the fight against human trafficking, see:

Bliss, N. et al.  (2021).  CCC/Code 8.7: Applying AI in the Fight Against Modern Slavery.  https://arxiv.org/abs/2106.13186

An algorithm to identify similarities across escort ads, making it easier for law enforcement to identify human traffickers, see: Carnegie Mellon University.  (2021).  Algorithm Uses Online Ads To Identify Human Traffickers.  https://www.ml.cmu.edu/news/news-archive/2021-2025/2021/april/machine-learning-ai-algorithm-uses-online-ads-identify-human-traffickers.html

Algorithms to extract signatures in images, such as specific tattoo designs linked to human trafficking networks, see: MIT News.  (2021).  Turning technology against human traffickers.  https://news.mit.edu/2021/turning-technology-against-human-traffickers-0506

Using AI to reveal trends in payments and help identify victims of modern slavery, see: World Economic Forum.  (2020).  How AI can help combat slavery and free 40 million victims.  https://www.weforum.org/agenda/2020/11/how-ai-can-help-combat-modern-slavery/

Examples of the work done by the Stanford Human Trafficking Data Lab to combat human trafficking, see: Stanford University.  (2021).  Melding Artificial Intelligence and Algorithms with Health Care and Policy to Combat Human Trafficking.  https://fsi.stanford.edu/news/melding-ai-and-algorithms-health-care-and-policy-combat-human-trafficking

[2]

For an index of governance in Africa see: Mo Ibrahim Foundation.  (2020).  2020 Ibrahim Index of African Governance: Key Findings.  https://mo.ibrahim.foundation/news/2020/2020-ibrahim-index-african-governance-key-findings

For a global comparison across various governance indicators see: The Worldwide Governance Indicators project.  (2020).  Worldwide Governance Indicators.  https://info.worldbank.org/governance/wgi/

With an average score of 32, Sub-Saharan Africa is the lowest performing region on the Transparency International Corruption Perceptions Index, see: Transparency International.  (2021).  CPI 2020: Sub-Saharan Africa.  https://www.transparency.org/en/news/cpi-2020-sub-saharan-africa

About the Author:

Gregg Barrett is a seasoned executive with extensive and diverse experience in strategy, building and managing relationships, deal-making, communication, developing high-performance teams, organisational leadership, and problem-solving across a range of areas. Over the last decade, Gregg has led work in data science, machine learning, corporate research, and corporate venture capital. This includes the establishment and management of data science, machine learning, corporate research, and corporate venture capital operations, working across people, processes, and technology, integrating structured and unstructured data to direct research, business, and investment strategy.

Der Beitrag A Sound of Hope for South Africa in the Fight Against Trafficking with AI erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: venturebeat.com – “How AI Innovation Can Drive 10X Growth in Enterprises – David Shrier Interview”

Shrier, who did a fireside chat with me at an AI event in San Francisco at ServiceNow, is a globally recognized expert on technology-driven innovation. He is a professor of practice in AI & Innovation with Imperial College Business School, and is a Visiting Scholar in the Department of Engineering at MIT.

And his Visionary Future venture studio invests in a portfolio of university-related spinouts spanning cognitive technologies, new financial architectures and sustainability, and is in the process of launching three new AI businesses over the next 90 days. Visionary Future published a report dubbed Artificial Intelligence Leadership Playbook.

David also has worked with over 100 governments on technology policy & regulation, and served on the parliamentary advisory committee for the EU AI Act. He has published eight books in the past eight years. His ninth book, Basic AI: A Human Guide to Artificial Intelligence, will be released by Little Brown and Harvard Business Publishing in January 2024.

David’s latest hack is ChatDave.AI (http://chatdave.ai), an LLM-based model that ingested about 600,000 words of his writing — essentially all of his books — on AI, cyber security, digital identity and blockchain.

In our fireside chat, Shrier started out with a discomforting thought, as he said that the importance of generative AI is “both less than people say it is and more than people realize it is.” While some talk of the elimination of jobs is incendiary (like the British Telecom CEO saying he’ll fire 42% of staff and replace them with AI), Shrier believes generative AI will drive some very real changes in workforce and society.[…]

Read more: www.venturebeat.com

Der Beitrag How AI Innovation Can Drive 10X Growth in Enterprises – David Shrier Interview erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.