EU puts up AI and data strategies with an ethical twist

The European Union (EU) has launched strategies for artificial intelligence (AI) and the “data economy”, with ethics and transparency as watchwords. It has also presented what it calls the “human-centric development of AI” as critical to “fighting climate change”.

The European Commission (EC) said in a statement that it favours a “European society powered by digital solutions that put people first, open up new opportunities for businesses, and boost the development of trustworthy technology to foster an open and democratic society and a vibrant and sustainable economy”.

Ursula von der Leyen, president of the EC, said: “Today we are presenting our ambition to shape Europe’s digital future. It covers everything from cyber security to critical infrastructures, digital education to skills, democracy to media. I want that digital Europe to reflect the best of Europe – open, fair, diverse, democratic and confident.”

Margrethe Vestager, executive vice-president for “A Europe fit for the digital age”, said in the same statement: “We want every citizen, every employee, every business to stand a fair chance to reap the benefits of digitisation, whether that means driving more safely or polluting less thanks to connected cars, or even saving lives with AI-driven medical imagery that allows doctors to detect diseases earlier than ever before.”

And Thierry Breto, commissioner for the internal market, added: “Our society is generating a huge wave of industrial and public data, which will transform the way we produce, consume and live. I want European businesses and our many SMEs [small and medium-sized enterprises] to access this data and create value for Europeans – including by developing AI applications. Europe has everything it takes to lead the ‘big data' race, and preserve its technological sovereignty, industrial leadership and economic competitiveness to the benefit of European consumers.”

The EC has said it will “focus on three key objectives in digital: technology that works for people, a fair and competitive economy, and an open, democratic and sustainable society”.

It added: “Europe has all it needs to become a world leader in AI systems that can be safely used and applied. We have excellent research centres, secure digital systems and a robust position in robotics, as well as competitive manufacturing and services sectors, spanning from automotive to energy, from healthcare to agriculture.”

The statement emphasised trust as vital to AI, saying: “As AI systems can be complex and bear significant risks in certain contexts, building trust is essential. Clear rules need to address high-risk AI systems without putting too much burden on less risky ones. Strict EU rules for consumer protection, to address unfair commercial practices and to protect personal data and privacy, continue to apply.”

As regards high-risk AI scenarios, the EC continued: “For high-risk cases, such as in health, policing or transport, AI systems should be transparent, traceable and guarantee human oversight. Authorities should be able to test and certify the data used by algorithms as they check cosmetics, cars or toys.”

To this assertion that AI should be explainable, the EC added caveats about the need to guard against bias in the datasets used to create AI systems and urged caution in the use of facial recognition technology.

“Unbiased data is needed to train high-risk systems to perform properly, and to ensure respect of fundamental rights, in particular non-discrimination,” it said. “While today, the use of facial recognition for remote biometric identification is generally prohibited and can only be used in exceptional, duly justified and proportionate cases, subject to safeguards and based on EU or national law, the commission wants to launch a broad debate about which circumstances, if any, might justify such exceptions.”

The EC allied its AI strategy announcement with a declaration about Europe’s “data economy”. It again asserted: “Europe has everything it takes to become a leader in this new data economy: the strongest industrial base of the world, with SMEs being a vital part of the industrial fabric; the technologies; the skills; and now also a clear vision.”

The commission said it is aiming at “setting up a true European data space, a single market for data, to unlock unused data, allowing it to flow freely within the EU and across sectors for the benefit of businesses, researchers and public administrations”.

It added: “Citizens, businesses and organisations should be empowered to make better decisions based on insights gleaned from non-personal data. That data should be available to all, whether public or private, startup or giant.”

To do this, the EC said it will first set up a “regulatory framework regarding data governance, access and reuse between businesses, between businesses and government, and within administrations”, adding that it “means to make public sector data more widely available by opening up high-value datasets across the EU and allowing their reuse to innovate on top”.

It also said it will launch “sectoral-specific actions, to build European data spaces in, for instanc,e industrial manufacturing, the green deal, mobility or health”.

The White paper on artificial intelligence is open for public consultation until 19 May 2020.

Bob De Caux, vice-president, AI and RPA (robotic process automation) at Sweden-based IFS, said of the EU statement: “By choosing to focus their new AI rules on ethics and transparency, the EU is positioning its AI vision in a way that can help a broad range of established businesses rather than just startups, while differentiating itself from the approaches of the US and China.

“Many European SMEs in industries such as manufacturing have had difficulty in scaling AI, not due to a lack of cutting-edge innovation, but due to the change in mindset and processes required to fully embrace a new approach. While it is true that a trust-based approach is more of a narrative than a business model, it is crucial to these businesses overcoming some of the misapprehensions and hype around AI that have built up over the past few years, and demonstrating that although it is not a magic bullet, it can drive real value when implemented properly.

“In addition, concentrating on transparency does not have to be an innovation killer. Black box approaches such as deep learning are not always appropriate or even necessary for many of the problems facing businesses, so it is encouraging to see a focus on research combining machine learning algorithms with more classic symbolic, human-understandable approaches, which will be very important in industries requiring human oversight, such as healthcare.”