by Cecilia Bonefeld-Dahl, Director-General DIGITALEUROPE and Member of the AI HLEG

The European Union is uniquely positioned to take a leading role towards a human-centric approach for an Artificial Intelligence (AI) policy. By accelerating the development and use of AI algorithms and tools, we can also accelerate job creation and growth. Recent studies for example show that for each job that could disappear from digital transformation,  3.7 new jobs will be created.[1]

However, designing a new framework should require more incentive-based legislation to close the existing gap in AI. For example, only 10-25% of large to small enterprises are using big data analytics. A more alarming statistic is that 83% of private sector AI investments are happening outside Europe.[2] Europe must catch up and invest massively in training and skilling. This is the only way forward if we are serious about  empowering people for the future.

The increased use of AI already puts massive pressure on governments and companies to skill and reskill people for the future job market. If they are successful, it is a great chance for Europe to create an ecosystem of scale-ups that will develop innovative solutions addressing the fundamental challenges in society like climate change, environmental sustainability, access to efficient health care, social inclusion, life-long learning etc.

But to accelerate the uptake of AI we need to build trust and knowledge. This raises a need for common principles for the ethical and sustainable development and application of AI. In short, we need a strategy that underpins a human-centric approach and European values.

At DIGITALEUROPE, we have had many internal discussions with our Members and exchange of views with stakeholders and other trade associations on how to address these challenges. In our new ‘Recommendations for AI Policy’ paper, published on 7 November, we outline what we’ve learned. You can find it here.

The paper includes an annex with several use cases. For example, how big data analytics helps oncology research to process huge amounts of data for the development of gene therapy. Other examples include solutions such as tracking endangered species, improving agriculture, and ensuring our roads and railways run safely.

The European Union has a key role to play in forming a platform for discussion, and to put in practice a robust AI industrial strategy – where one of the key priorities should be the quick take-up of AI solutions in European businesses and a massive skills programme.

The EU, national governments, industry, AI developers, labour and civil society will need to work together towards a responsible, ‘trusted AI’ framework, ensuring values and ethics in design and implementation while fostering innovated solutions and applications.

I look forward to working together with everyone towards these objectives!

[1]https://www.agoria.be/en/Agoria-Without-a-suitable-policy-there-will-be…

[2]https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced%20Electro…