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.

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SwissCognitive Guest Blogger: Zachary Amos – “How AI Will Impact 2024 Elections”

Generative artificial intelligence — models that can create images, videos, audio or text — have become incredibly popular because they’re widely available, easy to use and fast. Unfortunately, their greatest features are also threats. Will this technology permanently improve elections or unfairly sway the polls in one candidate’s favor?

AI’s Impact on Elections Is Global

2024 is a pivotal election year — not just for the United States but the world. Residents of over 50 countries will visit the polls this year alone, including Mexico, South Korea, the United Kingdom, India, South Africa, Taiwan and the European Union.

While most voters have come to expect — and know how to spot — attack ads, online trolling and misinformation around election time, AI has brought the world into uncharted waters. Generative models can create convincing images and videos with only one minute of audio or a few lines of text.

An AI-generated deepfake — real content that has been digitally manipulated with AI — is another massive concern. This technology replaces one person’s likeness or voice with a synthetic alternative.

According to one recent survey, about 78% of people believe bad actors will use AI to influence the U.S. presidential election outcome, with 70% thinking they’ll generate fake information and 62% assuming they’ll convince people not to vote.

AI’s Negative Impacts on Elections

There’s no downplaying AI’s negative impacts on elections.

Disinformation

Most people learn about candidates and current events from social media and internet headlines. In the United States, 82% of adults get their daily news from a digital device. This is an issue in an age where bad actors can create AI-generated disinformation almost instantly.

The Center for Countering Digital Hate, a British nonprofit, recently tested six of the leading AI voice cloning tools. Each produced fake audio snippets of high-profile politicians, with 80% of the tests generating a convincing clip.

Algorithmic Bias

AI systems can learn to make biased decisions if their training data contains skewed or inaccurate information or variables like gender, age, race or sexuality. Algorithms could act with prejudice if governments use this technology to accelerate vote counting or check voter eligibility.

Deepfakes

Divyendra Singh Jadoun is known as the “Indian Deepfaker” for his work on Bollywood clips and TV commercials. Recently, he claimed hundreds of Indian politicians sought his services ahead of the country’s elections, with 50% making unethical requests like defamation or deception. He says he denied them but doesn’t doubt others would accept their offers.

A deepfake can place a politician’s likeness over any body, face and voice to make it seem like they said or did something they never have. Politicians can — and have — used fake videos to make their opponents less likable. They even use AI on themselves to cast doubt on any real wrongdoings that might surface, giving them plausible deniability.

Fake Accounts

AI-powered social media bots spread misinformation and subconsciously influence voters by posting comments, sharing articles, and liking posts about certain politicians or upcoming elections.

Examples of AI Impacting Elections

AI’s effect on elections isn’t just hypothetical — it’s already happening. Of the 112 national elections in the United Kingdom between 2023 and 2024, 19 show signs of AI interference so far. When considering the evidence of AI-generated disinformation, that figure increases.

In Slovakia, days before the election — which was to determine who would lead the country — an audio clip of one of the leading candidates spread online. In it, he bragged about rigging the election. His opponent ended up defeating him.

In the United States, a former political consultant robocalled New Hampshire voters with an AI-generated voice meant to mimic President Biden, directing them not to vote. It reached thousands of people just ahead of the presidential primary. The man faces criminal and felony charges, along with a steep $6 million fine issued by the Federal Communications Commission.

Although the number of voters influenced in these situations remains unclear, one thing is certain — they were affected by AI interference. Going forward, cases like these aren’t going to be outliers. Instead, they may become as routine as attack ads and fake news posts.

AI’s Positive Impacts on Elections

It turns out AI might not be all bad — it still stands to positively impact the election.

Heightened Awareness

People aware of AI’s capabilities may be more likely to approach social media posts, news articles and viral clips with greater skepticism. Their newfound tendency to fact-check content can protect them from disinformation.

Election Administration

AI-powered systems could help administer elections, accelerating the time it takes to count votes, register voters or remind the general public of upcoming election dates. Considering these processes are typically so time-consuming, streamlining and automating them could be substantially beneficial.

Voter Education

Governments can offer AI tools to help voters stay informed. A machine learning model can pull up the latest news, fact-check social media posts, summarize news articles or identify AI-generated content.

AI-Generated Content Will Influence Elections

While rampant disinformation around election time isn’t new, it was obvious to those who could spot the telltale signs of Photoshop or traditional digital manipulation tactics. Now, generative models have muddied the waters. How can people tell what’s real anymore? What happens when politicians shrug off real scandals as some AI-generated hoax?

The question isn’t whether the AI’s positive impacts outweigh its negatives — it’s how to combat bad actors using this technology. Generative and machine-learning models are here to stay, so voters, governments and politicians should work together to figure out how to handle them. Swift, collaborative action may soon be the only thing ensuring fair elections.

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 Could Impact The 2024 Elections erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Global AI Ventures Shaping the Future – SwissCognitive AI Investment Radar

As AI’s impact resonates from the bustling tech hubs of Silicon Valley to the strategic marketplaces of Asia and Europe, demonstrating its unparalleled potential to reshape industries and economies.

This week, we explore significant movements in the AI sector that highlight the diverse applications and growing confidence in artificial intelligence technologies worldwide. From Google’s strategic AI security enhancements to Elon Musk’s ambitious fundraising for his AI venture, the landscape is vibrant with activity.

Microsoft’s hefty investment in the Emirati AI firm G42 and Meta’s unveiling of a new AI chip are testaments to the deepening integration of AI in corporate strategies. Meanwhile, regions like South Korea and the European Union are reinforcing their AI ambitions with substantial investments and groundbreaking legislation, respectively.

Further, Amazon’s commitment to infuse AI into its European operations reflects the growing trend of leveraging AI to enhance operational efficiencies and customer experiences. Each of these developments not only underscores the rapid evolution of AI technologies but also highlights the strategic dimensions of AI investments that are becoming crucial for maintaining competitive edges in the global market.

Join us as we delve into these exciting developments that illustrate how deeply AI is woven into the fabric of global economic strategies, driving innovation, efficiency, and growth. Stay tuned to SwissCognitive’s AI Investment Radar to keep abreast of how AI investments continue to unfold and transform the global landscape.

Previous SwissCognitive AI Investments Radar: The AI World Tour.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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The Billion-Dollar AI Investment Race – SwissCognitive AI Investment Radar

Our exploration begins with LG Group’s massive 74 billion-dollar pledge to AI development in South Korea, a move that heralds a future where technology drives growth and innovation. This ambitious investment underlines South Korea’s vision to become a global tech powerhouse.

Financial circles are buzzing about AI’s underestimated long-term economic impact. As OpenAI races towards a potential trillion-dollar valuation, the industry’s gaze shifts to AI’s transformative capabilities and its ability to redefine markets.

In Shanghai, a 13.8 billion-dollar fund aims to catapult startups in AI and biotech into the global arena, demonstrating China’s assertive push in tech innovation. Meanwhile, Cognition Labs seeks a $2 billion valuation for its AI code-writing tool, highlighting the increasing demand for AI-driven productivity enhancements.

Venture capital fervor mirrors this optimism, with nearly $100 million earmarked for AI startups by Superset, showcasing the sector’s potential for redefining technology’s future.

As we navigate through these groundbreaking developments and strategic investments, it’s evident that the journey of AI is not just about technology. It is also about shaping the future where innovation and human ambition converge, setting new frontiers for growth and possibilities.

Join the SwissCognitive AI Investment Radar and learn the latest news to stay updated in the fast-changing world of AI and Investments.

Previous SwissCognitive AI Investments Radar: Next-Gen AI Innovations And Investments.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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copyright by: https://asiatimes.com

The world is in a race to respond to Covid-19. This pandemic has disrupted societies, and continues to do so. Global economies are faltering; life as we know it has been put on hold. Trade and commerce have adapted, travel is restricted, and how we keep close to our communities and loved ones continually evolves.

The United Nations Conference on Trade and Development (UNCTAD) estimates that the economic impact of Covid-19 globally will be at least US$1 trillion this year.

In this unprecedented moment, technology is playing a transformative role in the world’s response to Covid-19. Emerging technologies are being developed and deployed at an extraordinary pace. Artificial intelligence (AI), big data and analytics have enabled innovative, rapid and wide-ranging responses to public health and essential-service delivery.

When economies reboot, and we emerge from self-isolation or lockdown, entrepreneurial ideas born on our sofas will need the freedom, space and support to scale up quickly. The next Asian unicorn is probably being hatched in a small town somewhere. Those ideas, big or small, will need the right digital ecosystem that supports an entrepreneurial response to flourish, not to flounder.

Heavily impacted sectors like tourism must be sustained through tough times to retain skills and bolster industry recovery. International cooperation, public-private partnerships, and technology-driven innovation will be essential to support the economic impact of these sectors for the good of all economies. 

Across Asia, technology at large is supporting business continuity, delivery of public and social services, information sharing, education, and connection for communities and families, amid significant disruption. 

Policy shifts to unlock opportunity

Led by the heroic efforts of essential workers, public health policy is in the process of being altered forever. Technology has played a role in helping stretched public health systems manage caseloads, enabling supply chains, connecting health workers to patients, facilitating telemedicine services for rural and affected communities, and supporting digital health tools. 

Governments across Asia are using digital technology to drive parts of their response. In Singapore and South Korea, for example, wide-scale screening, tracing and mapping efforts are finding success in containing transmission. Indonesia has followed this lead, while Malaysia has enabled citizens to assess individual health risks to support monitoring efforts.  

Scientists and researchers are navigating voluminous amounts of global health data, securely and at speed using cloud, data analytics and AI. These technologies are also accelerating scientific and medical analysis and experiments that would otherwise take years of human effort. Information sharing, rapid response technology, and access to innovation should become global health assets and not country-specific ones.

Education went from the classroom to the living room overnight. This seismic shift, enabled by the Internet and digital platforms, has helped learning to continue. However, hard questions on Internet access, investment in teachers and the broader role of technology must be asked and answered.

As the physical movement of goods and people becomes increasingly restricted around the world, technology such as cloud is a powerful lower-cost option for small businesses. At the same time, digital e-commerce and ride-hailing platforms are a lifeline for food, medicine and essential services.

With social distancing increasingly practiced globally, working from home is the new norm, enabled by cloud-based videoconferencing services and collaboration tools. Responding to this new paradigm of work will require business, government and community to embrace new practices.

Paramount to ensuring that technology can contribute even more will require governments to rethink digital policies and regulations in order to remove barriers and reduce burdens. This will be critical for key areas like e-commerce, payments, cross-border data flows, security, and privacy. Digital integration is a must.

There will be many competing priorities for government attention, investment and regulation in the months and years ahead. Technology companies are willing to play a critical role in the rebuilding phase. Public-private partnerships must be deepened to enable this.

Read more: https://asiatimes.com

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Copyright by www.forbes.com

So it’s only fitting that Kim, cofounder of Superb AI, has been selected as the featured honoree for the Enterprise Technology category of this year’s Forbes 30 Under 30 Asia list, leading a pack of several fellow honorees who founded startups based on AI. Since launching Superb AI in April 2018 with four cofounders, Kim has grown his startup to $2 million in revenues last year and 21 employees, fueled by increasing demand for AI. Profits are still in the future, but Superb AI also managed last year to join Y Combinator, a prominent Silicon Valley startup accelerator. So far, it has raised $2 million in funding from Y Combinator, Duke University and VC firms in Silicon Valley, Seoul and Dubai, giving it a valuation of $12 million as of March 2019.

Superb AI helps companies create and manage the huge amounts of customized datasets they need to build algorithms. “We wanted to solve these problems and lower the hurdle for industries to adopt machine-learning technology,” says Kim.

The inspiration for Superb AI came to Kim while he was pursuing a Ph.D. in robotics and AI at Duke University. When companies work on a machine-learning project, data must be manually labeled in order to train a computer in the algorithms—an expensive, laborious and error-prone process. “This is partly because building a deep learning system requires extreme amounts of labeled data that involve labor-intensive manual work and because a standalone AI system is not accurate enough to be fully trusted in most situations,” says Kim, who dropped out of the Ph.D. program to focus on Superb AI.

Superb AI uses deep learning AI to label and analyze images and videos up to 10 times faster than manual processes can, Kim says. About 30 companies already use Superb AI’s platform, mostly small businesses but also Samsung, LG, Qualcomm and Pokémon Go maker Niantic.

Now Kim is looking to expand further in North America and enter Europe. “We believe that AI should be widely adopted and used as a commodity across all industries to truly empower humans,” says Kim. “And we will make it happen.”

According to a McKinsey & Company report, about half of the 2,135 business leaders it surveyed in 2018 across various sectors said their companies deployed at least one AI-based system into its business. Another McKinsey report in 2018 estimates that AI could add around $13 trillion by 2030 to the current global economic output.

Hong Kong-based Gerardo Salandra is one of the business leaders contributing to the AI-driven economic growth. Salandra is cofounder and CEO of Rocketbots, an AI-powered chat automation platform for customer engagement. The AI element allows Rocketbots to learn messages in more than 15 languages, including English, Spanish and Chinese, then suggest a response to speed up conversations with customers.

According to Rocketbots, more than 10,000 companies use the platform, including Accenture, AXA and PricewaterhouseCoopers. Salandra is also the president of the Artificial Intelligence Society of Hong Kong, an association with more than 4,000 members dedicated to the development of AI and adoption of the technology.

Transforming Industries

One of the industries where AI is playing a big tangible role and driving transformation is finance. Last year, financial-services firms invested an estimated $5.6 billion on AI, according to research firm IDC, second only to the retail industry, which is estimated to have spent $5.9 billion.

Founded by Ashish Airon, CogniTensor is an example of how AI is being utilized in finance. The startup uses AI mainly to predict prices of commodities and energy. CogniTensor is working with India’s largest power trader, the state-owned Power Trading Corp., to help it with its power procurement strategies. In commodities, it started off with predicting prices for aluminum. Airon is also a member of the WHO – ITU Focus Group working on standardizing AI for health solutions.

AI technology is not just being used to improve business operations, but also for sustainable development. 30 Under 30 Asia list honorees Ayushi Mishra and Utkarsh Singh are doing just that.

The duo cofounded DronaMaps, a startup operating an AI-powered platform that creates and analyzes 3D maps to develop cities, villages and neighborhoods with pipeline planning, precision agriculture and flood mitigation, among others. Since its launch in 2016, it has mapped 600 square kilometers across six states in India. DronaMaps has worked with governments, universities and companies, including Reliance Industries, SAP and Johns Hopkins University. […]

Read more – www.forbes.com

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Copyright by spectrum.ieee.org

Drug development typically takes at least decade to move from idea to market, with failure rates of over 90% and a price tag between $2 and $3 billion. “We can substantially accelerate this process using AI and make it much cheaper, faster, and more likely to succeed,” says Alex Zhavoronkov, CEO of Insilico Medicine, an AI company focused on drug discovery.

Here’s an update on five AI-centered companies targeting coronavirus:

Deargen

In early February, scientists at South Korea-based Deargen published a preprint paper (a paper that has not yet been peer-reviewed by other scientists) with the results from a deep learning-based model called MT-DTI . This model uses simplified chemical sequences, rather than 2D or 3D molecular structures, to predict how strongly a molecule of interest will bind to a target protein.

The model predicted that of available FDA-approved antiviral drugs, the HIV medication atazanavir is the most likely to bind and block a prominent protein on the outside of SARS-CoV-2, the virus that causes COVID-19. It also identified three other antivirals that might bind the virus.

While the company is unaware of any official organization following up on their recommendations, their model also predicted several not-yet-approved drugs, such as the antiviral remdesivir , that are now being tested in patients, according to Sungsoo Park , co-founder and CTO of Deargen.

Deargen is now using their deep learning technology to generate new antivirals, but they need partners to help them develop the molecules, says Park. “We currently do not have a facility to test these drug candidates,” he notes. “If there are pharmaceutical companies or research institutes that want to test these drug candidates for SARS-CoV-2, [they would] always be welcome.”

Insilico Medicine

Hong Kong-based Insilico Medicine similarly jumped into the field in early February with a pre-print paper. Instead of seeking to re-purpose available drugs, the team used an AI-based drug discovery platform to generate tens of thousands of novel molecules with the potential to bind a specific SARS-CoV-2 protein and block the virus’s ability to replicate. A deep learning filtering system narrowed down the list.

“We published the original 100 molecules after a 4-day AI sprint,” says Insilico CEO Alex Zhavoronkov. The group next planned to make and test seven of the molecules, but the pandemic interrupted: Over 20 of their contract chemists were quarantined in Wuhan.

Since then, Insilico has synthesized two of the seven molecules and, with a pharmaceutical partner, plans to put them to the test in the next two weeks, Zhavoronkov tells IEEE. The company is also in the process of licensing their AI platform to two large pharmaceutical companies.

Insilico is also actively investigating drugs that might improve the immune systems of the elderly—so an older individual might respond to SARS-CoV-2 infection as a younger person does, with milder symptoms and faster recovery—and drugs to help restore lung function after infection. They hope to publish additional results soon.

SRI Biosciences and Iktos

On March 4, Menlo Park-based research center SRI International and AI company Iktos in Paris announced a collaboration to discover and develop new anti-viral therapies. Iktos’s deep learning model designs virtual novel molecules while SRI’s SynFini automated synthetic chemistry platform figures out the best way to make a molecule, then makes it.

With their powers combined, the systems can design, make and test new drug-like molecules in 1 to 2 weeks, says Iktos CEO Yann Gaston-Mathé. AI-based generation of drug candidates is currently in progress, and “the first round of target compounds will be handed to SRI’s SynFini automated synthesis platform shortly,” he tells IEEE.

Iktos also recently released two AI-based software platforms to accelerate drug discovery: one for new drug design, and another, with a free online beta version, to help synthetic chemists deconstruct how to better build a compound. “We are eager to attract as many users as possible on this free platform and to get their feedback to help us improve this young technology,” says Gaston-Mathé.

Benevolent AI

In February, British AI-startup Benevolent AI published two articles, one in The Lancet and one in The Lancet Infectious Diseases, identifying approved drugs that might block the viral replication process of SARS-CoV-2.

Using a large repository of medical information, including data extracted from the scientific literature by machine learning, the company’s AI system identified 6 compounds that effectively block a cellular pathway that appears to allow the virus into cells to make more virus particles.

One of those six, baricitinib, a once-daily pill approved to treat rheumatoid arthritis, looks to be the best of the group for both safety and efficacy against SARS-CoV-2, the authors wrote. Benevolent’s co-founder, Ivan Griffin, told Recode that Benevolent has reached out to drug manufacturers who make the drug about testing it as a potential treatment.

Currently, ruxolitinib, a drug that works by a similar mechanism, is in clinical trials for COVID-19.

Read more – spectrum.ieee.org

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Copyright by Aline Bassin

This is not an avant-garde algorithmic advance intended to generalize the use of autonomous cars. Even less than a revolutionary drug that a computer would have made alone in a laboratory. No, the first patent application filed for an artificial intelligence (AI) concerns a food container. What is special about this box? Its shape, called fractal, was imagined by the creativity machine of the American laboratory Imagine-Engines. The European Patent Office rejected in December the two patent applications associated with this innovation, recalling that it limits its sphere of protection to breakthroughs made by human beings.

A logical decision

Long awaited, this verdict does not surprise anyone. “The requester likely wanted to provoke debate,” said Philippe Schmitt, of the Parisian law firm Philippe Schmitt Avocats, specialized in intellectual property. “He could very easily have attributed his invention to a human being, while other cases are much more difficult to decide.”

The European Patent Office indeed confirms a growing demand for protection linked to AI, an evolution which poses new challenges: “Deciding on this type of innovation is more complicated,” observes Philippe Schmitt, “because computers are able to follow logic completely foreign to a human being. They are therefore very difficult to assess. “Also specializing in patent law, German and European patent attorney Michael Fischer of Venner Shipley LLP adds:” When you protect this type of technology, it can then possibly be difficult to prove that the patent has been infringed.”

Risks of crowding out human beings

Assigning patents to machines will not resolve any of these issues, say the two experts, who have no doubt that the competent authority in the United States, also called upon, will reserve an identical fate at the application of the American laboratory. “Acceptance could be dangerous,” warns Michael Fischer. Today, a company can file a patent application, but the invention must always be associated with men or women who must be explicitly mentioned on the application. And they are paid for it. ”

Director of the AI laboratory at EPFL, Boi Faltings agrees with this, noting that, even if it is not optimal, the current system makes sense: “The patent makes it possible to reward and protect the work of the author of an invention, while immediately revealing its contours, then making it available to everyone after a certain number of years. This approach contributes to widely disseminating scientific knowledge and developing know-how.”

A broader reflection on the status of machines

However, we cannot completely exclude an evolution in a more distant future. “First limited to human beings only, authorship has evolved in the 20th century to be recognized as originating in legal persons, which would have been unthinkable for authors like Apollinaire or Hugo ”, recalls Philippe Schmitt. Aware of the importance of the issue, the European Patent Office launched a vast reflection on the theme. “It emerged that the current system works pretty well, ”sums up his press office in an email. This specifies that the evolution of the situation is closely followed, in concert with other countries such as South Korea, the United States and the China.

 “The American Imagine-Engines laboratory seems to have been wrong of interlocutor and debate, concludes Michael Fischer who follows closely the protection of AI. His thinking is part of the much broader issue of rights and duties that one day could be conferred on machines. It’s a political issue. If that were the case, we could then discuss the advisability of attributing inventorship to them.”

A prospect that the expert does not see materialize in the near future, because the integration of artificial intelligence takes more time than expected. This discipline, born in the 1950s, experienced a long winter from the 1980s, before finding new life in the 21st century.

Read the original article – Le Temps

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Artificial Intelligence Software System Market Report by Material, Application, and Geography – Global Forecast to 2024 is a professional and in-depth research report on the world’s major regional Artificial Intelligence Software System Market conditions, focusing on the main regions (North America, Europe and Asia-Pacific) and the main countries (United States, Germany, united Kingdom, Japan, South Korea and China).

About Artificial Intelligence Software System Industry

The overviews, SWOT analysis and strategies of each vendor in the Artificial Intelligence Software System market provide understanding about the market forces and how those can be exploited to create future opportunities.

Key Players in this Artificial Intelligence Software System market are:–

Google
Baidu
IBM
Microsoft
SAP
Intel
Salesforce
Brighterion
KITT.AI
IFlyTek
Megvii Technology
Albert Technologies
H2O.ai
Brainasoft
Yseop
Ipsoft
NanoRep(LogMeIn)
Ada Support
Astute Solutions
IDEAL.com
Wipro

Production Analysis: SWOT analysis of major key players of Artificial Intelligence Software System industry based on a Strengths, Weaknesses, company’s internal & external environments. …, Opportunities and Threats. . It also includes Production, Revenue, and average product price and market shares of key players. Those data are further drilled down with Manufacturing Base Distribution, Production Area and Product Type. Major points like Competitive Situation and Trends, Concentration Rate Mergers & Acquisitions, Expansion which are vital information to grow/establish a business is also provided.

Application of Artificial Intelligence Software System Market are:

–

Product Segment Analysis of the Artificial Intelligence Software System Market is:

On-Premise

Cloud-based

This research report consists of the world’s crucial region market share, size (volume), trends including the product profit, price, Value, production, capacity, capability utilization, supply, and demand and industry growth rate.

Geographically this report covers all the major manufacturers from India, China, USA, UK, and Japan. The present, past and forecast overview of Artificial Intelligence Software System market is represented in this report.

Key Highlights of the Report:

• Historical data of Global Artificial Intelligence Software System Market for the Period 2015-2017

• Market Size & Forecast of Global Artificial Intelligence Software System Market until 2024

• Historical data of European Artificial Intelligence Software System Market for the Period 2015-2017

• Market Size & Forecast of European Artificial Intelligence Software System Revenue Market until 2024 […]

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Der Beitrag Global Artificial Intelligence Software System Report, By Development, Trends, Investigation 2019 and Forecast To 2024 erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.