FRA’s report is titled Getting The Future Right and opens with some of the ways AI is already making lives better—such as helping with cancer diagnosis, and even predicting where burglaries are likely to take place.

“The possibilities seem endless,” writes Michael O’Flaherty, Director of the FRA, in the report’s foreword. “But how can we fully uphold fundamental rights standards when using AI?”

The FRA interviewed over a hundred public administration officials, private company staff, and a diverse range of experts, in a bid to answer that question.

With evidence of algorithms having biases which could lead to automating societal issues like racial profiling—it’s a question that needs answering if the full potential of AI is going to be unlocked for the whole of society.

O’Flaherty says:

“AI is not infallible, it is made by people – and humans can make mistakes. That is why people need to be aware when AI is used, how it works and how to challenge automated decisions. The EU needs to clarify how existing rules apply to AI. And organisations need to assess how their technologies can interfere with people’s rights both in the development and use of AI.

“We have an opportunity to shape AI that not only respects our human and fundamental rights but that also protects and promotes them.”

AI is being used in almost every industry in some form or another—if not already, it will be soon.

Biases in AI are more dangerous in some industries than others. Policing is an obvious example, but in areas like financial services it could mean one person being given a loan or mortgage compared to another.

Without due transparency, these biases could happen without anyone knowing the reasons behind such decisions—it could simply be because someone grew up in a different neighbourhood. Each automated decision has a very real human impact.

The FRA calls for the EU to:

• Make sure that AI respects ALL fundamental rights – AI can affect many rights – not just privacy or data protection. It can also discriminate or impede justice. Any future AI legislation has to consider this and create effective safeguards.
• Guarantee that people can challenge decisions taken by AI – people need to know when AI is used and how it is used, as well as how and where to complain. Organisations using AI need to be able to explain how their systems take decisions.
• Assess AI before and during its use to reduce negative impacts – private and public organisations should carry out assessments of how AI could harm fundamental rights.
• Provide more guidance on data protection rules – the EU should further clarify how data protection rules apply to AI. More clarity is also needed on the implications of automated decision-making and the right to human review when AI is used.
• Assess whether AI discriminates – awareness about the potential for AI to discriminate, and the impact of this, is relatively low. This calls for more research funding to look into the potentially discriminatory effects of AI so Europe can guard against it.
• Create an effective oversight system – the EU should invest in a more ‘joined-up’ system to hold businesses and public administrations accountable when using AI. Authorities need to ensure that oversight bodies have adequate resources and skills to do the job.

The EU has increased its scrutiny of “big tech” companies like Google in recent years over concerns of invasive privacy practices and abusing their market positions. Last week, AI News reported that Google had controversially fired leading AI ethics researcher Timnit Gebru after she criticised her employer in an email.

Google chief executive Sundar Pichai wrote in a memo: “We need to accept responsibility for the fact that a prominent black, female leader with immense talent left Google unhappily.

“It’s incredibly important to me that our black, women, and under-represented Googlers know that we value you and you do belong at Google.”

Gebru gave an interview to the BBC this week in which she called Google and big tech “institutionally racist”. With that in mind, the calls made in the FRA’s report seem especially important to heed.

You can download a full copy of the FRA’s report here.

(Photo by Guillaume Périgois on Unsplash)

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Data from Dealroom was used for the State of European Tech report. Dealroom defines deep tech as 16 fields: Artificial Intelligence, Machine Learning, Big Data, Augmented Reality, Virtual Reality, Drones, Autonomous Driving, Blockchain, Nanotech, Robotics, Internet of Things, 3D Technology, Computer Vision, Connected Devices, Sensors Technology, and Recognition Technology (NLP, image, video, text, speech recognition).

In 2019, there was $10.2 billion capital invested in European deep tech. In 2020, that dropped to $8.9 billion:

I think it’s fair to say that 2020 has been a tough year for most people and businesses. Economic uncertainty – not just from COVID-19 but also trade wars, Brexit, and a rather tumultuous US presidential election – has naturally led to fewer investments and people tightening their wallets.

For just one example, innovative satellite firm OneWeb was forced to declare bankruptcy earlier this year after crucial funding it was close to securing was pulled during the peak of the pandemic. Fortunately, OneWeb was saved following an acquisition by the UK government and Bharti Global—but not all companies have been so fortunate.

Many European businesses will now be watching the close-to-collapse Brexit talks with hope that a deal can yet be salvaged to limit the shock to supply lines, prevent disruption to Europe’s leading financial hub, and help to build a friendly relationship going forward with a continued exchange of ideas and talent rather than years of bitterness and resentment.

The report shows the UK has retained its significant lead in European tech investment and startups this year:

Despite the uncertainties, the UK looks unlikely to lose its position as the hub of European technology anytime soon.

Investments in European tech as a whole should bounce back – along with the rest of the world – in 2021, with promising COVID-19 vaccines rolling out and hopefully some calm in geopolitics.

94 percent of survey respondents for the report stated they have either increased or maintained their appetite to invest in the European venture asset class. Furthermore, a record number of US institutions have participated in more than one investment round in Europe this year—up 36% since 2016.

You can find a full copy of the State of European Tech report here.

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Cambridge Analytica was accused in March 2018 of using AI tools and big data to influence the results of the Brexit referendum and the US presidential election. Most objective observers probably felt the case was overblown, but it’s taken until now to be confirmed.

“From my review of the materials recovered by the investigation I have found no further evidence to change my earlier view that CA [Cambridge Analytica] was not involved in the EU referendum campaign in the UK,” wrote Information Commissioner Elizabeth Denham.

Cambridge Analytica did obtain a ton of user data—but through predominantly commercial means, and of mostly US voters. Such data is available to, and has also been purchased by, other electoral campaigns for targeted advertising purposes (the Remain campaigns in the UK actually outspent their Leave counterparts by £6 million.)

“CA were purchasing significant volumes of commercially available personal data (at one estimate over 130 billion data points), in the main about millions of US voters, to combine it with the Facebook derived insight information they had obtained from an academic at Cambridge University, Dr Aleksandr Kogan, and elsewhere,” wrote Denham.

The only real scandal was Facebook’s poor protection of users which allowed third-party apps to scrape their data—for which it was fined £500,000 by the UK’s data protection watchdog.

It seems the claims Cambridge Analytica used powerful AI tools were also rather overblown, with the information commissioner saying all they found were models “built from ‘off the shelf’ analytical tools”.

The information commissioner even found evidence that Cambridge Analytica’s own staff “were concerned about some of the public statements the leadership of the company were making about their impact and influence.”

Cambridge Analytica appears to have been a victim of those unable to accept democratic results combined with its own boasting of capabilities that weren’t actually that impressive.

You can read the full report here (PDF)

(Photo by Christian Lue on Unsplash)

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Clearview AI’s facial recognition system is used by over 2,200 law enforcement agencies around the world and even commercial businesses like Best Buy and Macy’s, according to a recent leak.

The EDPB has now ruled that any use of the service by law enforcement in Europe would “likely not be consistent with the EU data protection regime.”

Furthermore, the watchdog “has doubts as to whether any Union or Member State law provides a legal basis for using a service such as the one offered by Clearview AI.”

Clearview AI scrapes billions of photos from across the internet for its powerful system, a practice which has come under fire by privacy campaigners. “Common law has never recognised a right to privacy for your face,” Clearview AI lawyer Tor Ekeland argued recently.

The American Civil Liberties Union (ACLU) launched a lawsuit against Clearview AI last month after calling it a “nightmare scenario” for privacy.

“Companies like Clearview will end privacy as we know it, and must be stopped,” said Nathan Freed Wessler, senior staff attorney with the ACLU’s Speech, Privacy, and Technology Project.

Aside from the company’s practices, concerns have been raised about Clearview AI’s extensive ties with the far-right. Ekeland himself has gained notoriety as “The Troll’s Lawyer” for defending clients such as neo-Nazi troll Andrew Auernheimer.

Backlash over Clearview AI forced the company to announce it will no longer offer its services to private companies. The EU’s ruling will limit Clearview AI’s potential customers even further.

Concerns have grown in recent weeks about facial recognition services amid protests over racial discrimination. Facial recognition services have been repeatedly found to falsely flag minorities; stoking fears they’ll lead to automated racial profiling.

IBM and Amazon have both announced this week they’ll no longer provide facial recognition services to law enforcement and have called on Congress to increase regulation to help ensure future deployments meet ethical standards.

(Photo by Christian Lue on Unsplash)

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Writing in a FT editorial, Pichai said: “…there is no question in my mind that artificial intelligence needs to be regulated. It is too important not to.”

Few people debate the need for AI regulation but there are differing opinions when it comes to how much. Overregulation limits innovation while lack of regulation can pose serious dangers – even existential depending on who you listen to.

Pichai says AI is “one of the most promising new technologies” that has “the potential to improve billions of lives,” but warns of the possible risks if development is left unchecked.

“History is full of examples of how technology’s virtues aren’t guaranteed,” Pichai wrote. “The internet made it possible to connect with anyone and get information from anywhere, but also easier for misinformation to spread.”

Google is one of the companies which people have voiced concerns about given its reach and questionable record when it comes to user privacy. Pichai’s words today will offer some comfort that Google’s leadership wants sensible regulation to guide its efforts.

So far, Google has shown how AI can be used for good. A study by Google, published in science journal Nature, showed how its AI model was able to spot breast cancer in mammograms with “greater accuracy, fewer false positives, and fewer false negatives than experts.”

Governments around the world are beginning to shape AI regulations. The UK, Europe’s leader in AI developments and investments, aims to focus on promoting ethical AI rather than attempt to match superpowers like China and the US in other areas.

In a report last year, the Select Committee on Artificial Intelligence recommended the UK capitalises on its “particular blend of national assets” to “forge a distinctive role for itself as a pioneer in ethical AI”.

The EU, which the UK leaves at the end of this month, recently published its own comprehensive proposals on AI regulation which many believe are too stringent. The US warned its European allies against overregulation of AI earlier this month.

In a statement released by the Office of Science and Technology Policy, the White House wrote:

“Europe and our allies should avoid heavy handed innovation-killing models, and instead consider a similar regulatory approach.

The best way to counter authoritarian uses of AI is to make sure America and our international partners remain the global hubs of innovation, shaping the evolution of technology in a manner consistent with our common values.”

Pichai refrains from denouncing either the White House’s calls for light AI regulation, or the EU’s plans for stringent rules. Instead, Pichai only calls for the need to balance “potential harms… with social opportunities.”

Google has certainly not been devoid of criticism over its forays into AI. The company was forced to back out from a Pentagon contract in 2018 called Project Maven over backlash about Google building AI technology for deploying and monitoring unmanned aerial vehicles (UAVs).

Following the decision to back out from Project Maven, Pichai outlined Google’s ethical principles when it comes to AI:

1. Be socially beneficial.
2. Avoid creating or reinforcing unfair bias.
3. Be built and tested for safety.
4. Be accountable to people.
5. Incorporate privacy design principles.
6. Uphold high standards of scientific excellence.
7. Be made available for uses that accord with these principles.

Pichai promised the company “will work to limit potentially harmful or abusive applications” and will block the use of their technology if they “become aware of uses that are inconsistent” with the principles.

Time will tell whether Google will abide by its principles when it comes to AI, but it’s heartening to see Pichai call for sensible regulation to help enforce it across the industry.

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While the news has gone somewhat under the radar given recent events, the Americans are concerned that overregulation may cause Western nations to fall behind the rest of the world.

In a statement released by the Office of Science and Technology Policy, the White House wrote:

“Europe and our allies should avoid heavy handed innovation-killing models, and instead consider a similar regulatory approach.

The best way to counter authoritarian uses of AI is to make sure America and our international partners remain the global hubs of innovation, shaping the evolution of technology in a manner consistent with our common values.”

The UK is expected to retain its lead as the European hub for AI innovation with vast amounts of private and public sector investment, successful companies like DeepMind, and world class universities helping to address the global talent shortage. In Oxford Insights’ 2017 Government AI Readiness Index, the UK ranked number one due to areas such as digital skills training and data quality. The Index considers public service reform, economy and skills, and digital infrastructure.

Despite its European AI leadership, the UK would struggle to match the levels of funding afforded to firms residing in superpowers like the US and China. Many experts have suggested the UK should instead focus on leading in the ethical integration of AI and developing sensible regulations, an area it has much experience in.

Here’s a timeline of some recent work from the UK government towards this goal:

• September 2016 – the House of Commons Science and Technology Committee published a 44-page report on “Robotics and Artificial Intelligence” which investigates the economic and social implications of employment changes, ethical and legal issues around safety, verification, bias, privacy, and accountability; and strategies to enhance research, funding, and innovation
• January 2017 – an All Party Parliamentary Group on Artificial Intelligence (APPG AI) was established to address ethical issues, social impact, industry norms, and regulatory options for AI in parliament.
• June 2017 – parliament established the Select Committee on AI to further consider the economic, ethical and social implications of advances in artificial intelligence, and to make recommendations. All written and oral evidence received by the committee can be seen here.
• April 2018 – the aforementioned committee published a 183-page report, “AI in the UK: ready, willing and able?” which considers AI development and governance in the UK. It acknowledges that the UK cannot compete with the US or China in terms of funding or people but suggests the country may have a competitive advantage in considering the ethics of AI.
• September 2018 – the UK government launched an experiment with the World Economic Forum to develop procurement policies for AI. The partnership will bring together diverse stakeholders to collectively develop guidelines to capitalise on governments’ buying power to support the responsible deployment and design of AI technologies.

Western nations are seen as being at somewhat of a disadvantage due to sensitivities around privacy. EU nations, in particular, have strict data collection regulations such as GDPR which limits the amount of data researchers can collect to train AIs.

“Very often we hear ‘Where are the British and European Googles and Facebooks?’ Well, it’s because of barriers like this which stop organisations like that being possible to grow and develop,” said Peter Wright, solicitor and managing director of Digital Law UK.

Dependent on the UK’s future trade arrangement with the EU, it could, of course, decide to chart its own regulatory path following Brexit.

Speaking to reporters in a call, US CTO Michael Kratsios said: “Pre-emptive and burdensome regulation does not only stifle economic innovation and growth, but also global competitiveness amid the rise of authoritarian governments that have no qualms with AI being used to track, surveil, and imprison their own people.”

In the same call, US deputy CTO Lynne Parker commented: “As countries around the world grapple with similar questions about the appropriate regulation of AI, the US AI regulatory principles demonstrate that America is leading the way to shape the evolution in a way that reflects our values of freedom, human rights, and civil liberties.

“The new European Commission has said they intend to release an AI regulatory document in the coming months. After a productive meeting with Commissioner Vestager in November, we encourage Europe to use the US AI principles as a framework. The best way to counter authoritarian uses of AI is to make America and our national partners remain the global hub of innovation, advancing our common values.”

A similar regulation to GDPR in California called CCPA was also signed into law in June 2018. “I think the examples in the US today at state and local level are examples of overregulation which you want to avoid on the national level,” said a government official.

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Feige had just finished giving a talk entitled ‘Fairness in AI: Latest developments in AI safety’ at this year’s AI Expo Global. We managed to grab him to get more of his thoughts on the issue.

Rightfully, people are becoming increasingly concerned about unfair and unsafe AIs. Human biases are seeping into algorithms which poses a very real danger that prejudices and oppression could become automated by accident.

AI News reported last week on research from New York University that found inequality in STEM-based careers is causing algorithms to work better or worse for some parts of society over others.

Similar findings, by Joy Buolamwini and her team from the Algorithmic Justice League, highlighted a disparity in the effectiveness of the world’s leading facial recognition systems between genders and skin tones.

In an ideal world, all parts of society would be equally represented tomorrow. The reality is that issue is going to take much longer to rectify, but AI technologies are becoming increasingly used across society today.

AI News asked Feige for his perspective and how the impact of that problem can be reduced much sooner.

“I think the most important thing for organisations to do is to spend more time thinking about bias and on ensuring that every model they build is unbiased because a demographically disparate team can build non-disparate tech.”

Some companies are seeking to build AIs which can scan for bias in other algorithms. We asked Feige for his view on whether he believes this is an ideal solution.

“Definitely, I showed one in my talk. We have tests for: You give me a black box algorithm, I have no idea what your algorithm does – but I can give an input, calculate the output, and I can just tell you how biased it is according to various definitions of bias.”

“We can go even further and say: Let’s modify your algorithm and give it back so it’s unbiased according to one of those definitions.”

In the Western world, we consider ourselves fairly liberal and protective of individual freedoms. China, potentially the world’s leader in AI, has a questionable human rights record and is known for invasive surveillance and mass data collection. Meanwhile, Russia has a reputation for military aggression which some are concerned will drive its AI developments. Much of the Middle East, while not considered leaders in AI, is behind most of the world in areas such as female and gay rights.

We asked Feige for his thoughts on whether these regional attitudes could find their way into AI developments.

“It’s an interesting question. It’s not that some regions will take the issue more or less seriously, they just have different … we’ll say preferences. I suspect China takes surveillance and facial recognition seriously – more seriously than the UK – but they do so in order to leverage it for mass surveillance, for population control.”

“The UK is trying to walk a fine line in efficiently using that very useful technology but not undermine personal privacy and freedom of individuals.”

During his talk, Feige made the point that he’s less concerned about AI biases due to the fact that – unlike humans – algorithms can be controlled.

“This is a real source of optimism for me, just because human decision-making is incredibly biased and everyone knows that.”

Feige asked the audience to raise a hand if they were concerned about AI bias which prompted around half to do so. The same question was asked regarding human bias and most of the room had their hand up.

“You can be precise with machine learning algorithms. You can say: ‘This is the objective I’m trying to achieve, I’m trying to maximise the probability of a candidate being successful at their job according to historical people in their role’. Or, you can be precise about the data the model is trained on and say: ‘I’m going to ignore data from before this time period because things were ‘different’ back then’”.

“Humans have fixed past experiences they can’t control. I can’t change the fact my mum did most of the cooking when I was growing up and I don’t know how it affects my decision-making.”

“I also can’t force myself to hire based on success in their jobs, which I try to do. It’s hard to know if really I just had a good conversation about the football with the candidate.”

Faculty, of which Feige has the role of head of research, is a European company based in London. With the EU Commission recently publishing its guidelines on AI development, we took the opportunity to get his views on them.

“At a high-level, I think they’re great. They align quite a bit with how we think about these things. My biggest wish, whenever a body like that puts together some principles, is that there’s a big gap between that level of guidelines and what is useful for practitioners. Making those more precise is really important and those weren’t precise enough by my standards.”

“But not to just advocate putting the responsibility on policymakers. There’s also an onus on practitioners to try and articulate what bias looks like statistically and how that may apply to different problems, and then say: ‘Ok policy body, which of these is most relevant and can you now make those statements in this language’ and basically bridge the gap.”

Google recently created, then axed, a dedicated ‘ethics board’ for its AI developments. Such boards seem a good idea but representing society can be a minefield. Google’s faced criticism for having a conservative figure with strong anti-LGBTQ and immigrant views on the board.

Feige provided his take on whether companies should have an independent AI oversight board to ensure their developments are safe and ethical.

“To some degree, definitely. I suspect there are some cases you want that oversight board to be very external and like a regulator with a lot of overhead and a lot of teeth.”

“At Faculty, each one of our product teams has a shadow team – which has practically the same skill set – who monitor and oversee the work done by the project team to ensure it follows our internal set of values and guidelines.”

“I think the fundamental question here is how to do this in a productive way and ensure AI safety but that it doesn’t grind innovation to a halt. You can imagine where the UK has a really strong oversight stance and then some other country with much less regulatory oversight has companies which become large multinationals and operate in the UK anyway.”

Getting the balance right around regulation is difficult. Our sister publication IoT News interviewed a digital lawyer who raised the concern that Europe’s strict GDPR regulations will cause AI companies in the continent to fall behind their counterparts in Asia and America which have access to far more data.

Feige believes there is the danger of this happening, but European countries like the UK – whether it ultimately remains part of the EU and subject to regulations like GDPR or not – can use it as an opportunity to lead in AI safety.

Three reasons are provided why the UK could achieve this:

1. The UK has significant AI talent and renowned universities.
2. It has a fairly unobjectionable record and respected government (Feige clarifies in comparison to how some countries view the US and China).
3. The UK has a fairly robust existing regulatory infrastructure – especially in areas such as financial services.

Among the biggest concerns about AI continues to be around its impact on the workforce, particularly whether it will replace low-skilled workers. We wanted to know whether using legislation to protect human workers is a good idea.

“You could ask the question a hundred years ago: ‘Should automation come into agriculture because 90 percent of the population works in it?’ and now it’s almost all automated. I suspect individuals may be hurt by automation but their children will be better off by it.”

“I think any heavy-handed regulation will have unintended consequences and should be thought about well.”

Our discussion with Feige was insightful and provided optimism that AI can be developed safely and fairly, as long as there’s a will to do so.

You can watch our full interview with Feige from AI Expo Global 2019 below:

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In the keynote session, titled ‘What is the true adoption of AI’, Hogan provided real-world examples of how the technology is being used and enabled by Nvidia’s GPUs. But first, he highlighted the momentum we’re seeing in AI.

“Many governments have announced investments in AI and how they’re going to position themselves,” comments Hogan. “Countries around the world are starting to invest in very large infrastructures.”

The world’s most powerful supercomputers are powered by Nvidia GPUs. ORNL Summit, the current fastest, uses an incredible 27,648 GPUs to deliver over 144 petaflops of performance. Vast amounts of computational power is needed for AI which puts Nvidia in a great position to capitalise.

“The compute demands of AI are huge and beyond what anybody has seen within a standard enterprise environment before,” says Hogan. “You cannot train a neural network on a standard CPU cluster.”

Nvidia started off by creating graphics cards for gaming. While that’s still a big part of what the company does, Hogan says the company pivoted towards AI back in 2012.

A great deal of the presentation was spent on autonomous vehicles, which is unsurprising given the demand and Nvidia’s expertise in the field. Hogan highlights that you simply cannot train driverless cars using CPUs and provided a comparison in cost, size, and power consumption.

“A new type of computing is starting to evolve based around GPU architecture called ‘dense computing’ – the ability to build systems that are highly-powerful, huge amounts of computational scale, but actually contained within a very small configuration,” explains Hogan.

Autonomous car manufacturers need to train petabytes of data per day, reiterate their models, and deploy them again in order to get those vehicles to market.

Nvidia has a machine called the DGX-2 which delivers two petaflops of performance. “That is one server that’s equivalent to 800 traditional servers in one box.”

Nvidia has a total of 370 autonomous vehicles which Hogan says covers most of the world’s automotive brands. Many of these are investing heavily and rushing to deliver at least ‘Level 2’ driverless cars in the 2020-21 timeframe.

“We have a fleet of autonomous cars,” says Hogan. “It’s not our intention to compete with Uber, Daimler or BMW, but the best way of us helping our customers enable that is by trying it ourselves.”

“All the work our customers do we’ve also done ourselves so we understand the challenges and what it takes to do this.”

Real-world impact

Hogan notes how AI is a “horizontal capability that sits across organisations” and is “an enabler for many, many things”. It’s certainly a challenge to come up with examples of industries that cannot be improved to some degree through AI.

Following autonomous cars, Nvidia sees the next mass scaling of AI happening in healthcare (which our dear readers already know, of course.)

Hogan provides the natural example of the UK’s National Health Service (NHS) which has vast amounts of patient data. Bringing this data together and having an AI make sense of it can unlock valuable information to improve healthcare.

AIs which can make sense of medical imaging on a par with, or even better, than some doctors are starting to become available. However, they are still 2D images that are alien to most people.

Hogan showed how AI is able to turn 2D imagery into 3D models of the organs which are easier to understand. In the GIF below, we see a radiograph of a heart being turned into a 3D model:

We’ve also heard about how AI is helping with the field of genomics, assisting in finding cures for human diseases. Nvidia GPUs are used for Oxford Nanopore’s MinIT handheld which enables DNA sequencing of things such as plants to be conducted in-the-field.

In a blog post last year, Nvidia explained how MinIT uses AI for basecalling:

“Nanopore sequencing measures tiny ionic currents that pass through nanoscale holes called nanopores. It detects signal changes when DNA passes through these holes. This captured signal produces raw data that requires signal processing to determine the order of DNA bases – known as the ‘sequence.’ This is called basecalling.

This analysis problem is a perfect match for AI, specifically recurrent neural networks. Compared with previous methods, RNNs allow for more accuracy in time-series data, which Oxford Nanopore’s sequencers are known for.”

Hogan notes how, in many respects, eCommerce paved the way for AI. Data collected for things such as advertising helps to train neural networks. In addition, eCommerce firms have consistently aimed to improve and optimise their algorithms for things such as recommendations to attract customers.

“All that data, all that Facebook information that we’ve created, has enabled us to train networks,” notes Hogan.

Brick-and-mortar retailers are also being improved by AI. Hogan gives the example of Walmart which is using AI to improve their demand forecasting and keep supply chains running smoothly.

In real-time, Walmart is able to see where potential supply challenges are and take action to avoid or minimise. The company is even able to see where weather conditions may cause issues.

Hogan says this has saved Walmart tens of billions of dollars. “This is just one example of how AI is making an impact today not just on the bottom line but also the overall performance of the business”.

Accenture is now detecting around 200 million cyber threats per day, claims Hogan. He notes how protecting against such a vast number of evolving threats is simply not possible without AI.

“It’s impossible to address that, look at it, prioritise it, and action it in any other way than applying AI,” comments Hogan. “AI is based around patterns – things that are different – and when to act and when not to.”

While often we hear about what AI could one day be used for, Hogan’s presentation was a fascinating insight into how Nvidia is seeing it making an impact today or in the not-so-distant future.

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Some of the highlighted risks includes lethal autonomous systems, tracking individuals, and ‘scoring’ people in society.

On the subject of lethal autonomous systems, the experts warn machines with cognitive skills could “decide whom, when and where to fight without human intervention”.

When it comes to tracking individuals, the experts foresee biometric data of people being involuntarily used such as “lie detection [or] personality assessment through micro expressions”.

Citizen scoring is on some people’s minds after being featured in an episode of dystopian series Black Mirror. The experts note that scoring criteria must be transparent and fair, with scores being challengeable

The guidelines have been several years in the making and have launched alongside a pilot project for testing how they work in practice.

Experts from various fields across Europe sit in the group, including academic lawyers from Birmingham and Oxford universities.

They concluded: “it is important to build AI systems that are worthy of trust, since human beings will only be able to confidently and fully reap its benefits when the technology, including the processes and people behind the technology, are trustworthy.”

The EU as a whole is looking to invest €20bn (£17bn) every year for the next decade to close the current gap between European developments and those in Asia and North America.

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A group of industry experts were appointed in 2016 to establish guidelines which ensure that AI is developed sensibly.

There are seven key pillars to the EU’s ethical AI strategy:

1. Human agency and oversight
2. Robustness and safety
3. Privacy and data governance
4. Transparency
5. Diversity, non-discrimination, and fairness
6. Societal and environmental well-being
7. Accountability

The EU wants to promote its guidelines on the global stage. It plans on strengthening cooperation with ‘like-minded’ partners such as Japan, Canada, and Singapore, while engaging in dialogue with the G7 and G20.

Mariya Gabriel, EU Commissioner for Digital Economy and Society, added:

“Today, we are taking an important step towards ethical and secure AI in the EU. We now have a solid foundation based on EU values and following an extensive and constructive engagement from many stakeholders including businesses, academia and civil society.

We will now put these requirements to practice and at the same time foster an international discussion on AI.”

Some experts have criticised the EU for its strict policies around the collection and processing of data, especially since GDPR came into effect.

Commenting on GDPR’s effect on AI startups for our sister publication IoT News, Digital Law UK Managing Director Peter Wright said:

“You’ve got your Silicon Valley startup that can access large amounts of money from investors, access specialist knowledge in the field, and will not be fighting with one arm tied behind its back like a competitor in Europe.

Very often we hear ‘Where are the British and European Googles and Facebooks?’ Well, it’s because of barriers like this which stop organisations like that being possible to grow and develop.”

While few debate the need for personal data to be protected, large amounts of it are needed for training AI models even if the data is anonymised.

Critics believe the EU’s strict policies will see the continent fall behind competitors such as the US and China; where data protection ranges from more lenient, to practically non-existent.

Afke Schaart, VP and Head of Europe at GSMA, welcomes the EU’s guidelines:

“The powerful combination of AI with 5G and The Internet of Things will transform entire industries and enable new disruptive services. Only with the right conditions will European companies be able to capture the full potential of AI and develop consumer trust in a new era of Intelligent Connectivity.

These guidelines are an important first step towards achieving the objective of unlocking innovation in AI while ensuring that acting ethically does not undermine Europe’s future competitiveness.

Members of the EU’s AI expert group will present their work tomorrow (April 8th) during the third ‘Digital Day’ in Brussels.

deepgeniusai.com/">AI & Big Data Expo events with upcoming shows in Silicon Valley, London, and Amsterdam to learn more. Co-located with the IoT Tech Expo, , & .

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