2020 - Manifesto for a European Agenda on Industrial AI - Orgalim: Europe's Technology Industries
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Recent technological advances put artificial intelligence (AI) at the forefront of industrial innovation - making AI a powerful enavler of the digital transformation across the technology sectors.
This is good news for Europe´s economy, as digital transformation - together with sustainability - is the main driver of industrial growth. It is estimated that AI could add over €2 trillion to the economy by 2030, as new solutions optimise manufacturing processes and boost productivity gains. And it´s good news for European society too, as AI technology can help deliver answers to challenges in areas from energy to healthcare to mobility and beyond.
A full two-thirds of the value created by AI is attributable to the bussiness-to-bussiness (B2B) sphere. This provides Europe with a world of opportunity, as our industries´strengths lie precisely in the space where long-standing industry expertise meets digital innovation. A further competitive edge is the European commitment to 'trustworthy AI': an approach to teach development that addresses both industrial and ethical dimesnsions, enshrined in a human-centric approach. This will be vital to gain citizens´ trust in new technology and accelarate uptake across sectors.
To fully unlock this potential for Europe, the right framework will be needed at EU level. There is no time to waste, with competitive pressure from the US and China rising day-by-day. This is why Orgalim-representing the technology companies spearheading industrial Ai development - is calling on EU policymakers to prioritise meausures to support Europe´s technology industries as providers of world leading trustworthy AI solutions for the global market.
WHAT IS INDUSTRIAL AI?
Many misconceptions surround AI, often based more on science fiction than fact. Given the reality of how the technology is used in industry today, one of the definitions most often used is the following:
AI refers to computer systems based on algorithms designed by humans that, given a complex task, operate by processing the structured or unstructured data collected in their environment according to a set of instructions, determining the best stpe(s) to take to perform the given task, via software or hardware actuators. AI computer systems can also adapt their actions by analysing how the environment is affected by their previous actions.
This definition - similiar to that given by the EU Commission´s High-Level Expert Group on AI-insists on the human origin of any AI and highlights the fact that machines can only perform an action assigned from the outset by humans.
ORGALIM REPRESENTS:
46 Associations
22 Countries
31 National member associations
15 European sector associations
3 Industries: mechanical engineering; electrical engineering, electronics and ICT; metal technology
Policy recommendations
Orgalim is calling for an EU-level strategy focused on trustworthy AI, addressing both the ethical and industrial dimensions, enshrined in human-centric approach. We believe that this will allow Europe to reap the full benefits of Ai innovation and to create a competitive differentiator for our industries in the global AI race.
To make it happen, urgent policy action is needed across a number of fronts. Drawing on the expertise of its members of AI innovation and create a competitive differentiator for our industries in the global AI race.
To make it happen, urgent policy action is needed across a number of fronts. Drawing on the expertise of its members - representing companies at the leading edge of industrial AI development across Europe - Orgalim has produced a 'Manifesto for a European agenda on industrial AI', in wich we outline our key recommendations for the future framework in the following four areas:
Strong Internal Market and legal framework
Safety and liability legislation supporting AI
Maintain current safety and liability legislation, wich is fit for purpose - including as regards AI development
Regulatory sandboxes
Develop a framework for the definition and governance of regulatory sandboxes at EU level in order to provide a harmonised approach in Member States
Data: unlocking the power of industrial data
Maintain that contracts rather than law should be the basis of data exchange and flow of data overall in B2B relationships - essential given the complexity of business cases in various value chains
Accompanying measures: investments in R&D and capital, innovation, skills
Public and private investment
Adopt the next EU Multiannual Financial Framework as soon as possible to allow for full deployment of the next series of EU funding and investment programmes in support of innovation
R&D programme focus
Focus European and national public research more strongly on AI applications in industry
Deployment and uptake
Facilitate deployment of AI throughout European industry as a whole
Education and skills
Launch an EU´master plan for training and education' to boost general education STEM, and develop curricula integrating digital and physical engineering
Fostering trust: ethics, privacy, security and dialogue
Ethical guidelines
Further develop ethical guidelines of the High-Level Expert Group on AI in collaboration with industry and use these as a basis to promote an international approach to trustworthy AI
GDPR implementation
Ensure general guidance by the Commission on proper GDPR implementation
Cybersecurity
Aim for a holistic approach to cybersecurity policy to ensure an enabling, consistent and coherent framework at EU level
Dialogue and exchange
Foster dialogue on AI between the social partners and with the public at large
A strong global outlook
International approach
An international approach towards trustworthy AI should be promoted by the EU and Member States
International standards
Work to develop internationally recognised and consensually created international standards for AI
As the EU enters a new legislative cycle, AI must remain a top policy priority if Europe is to unlock the potential of this future tech for our economy and society. Orgalim is calling for a strategy centred on trustworthy AI – addressing both the ethical and industrial dimensions, enshrined in a human centric approach. We believe these will be the critical elements to give Europe an edge in the global AI innovation race. The recommendations presented here can shape an enabling framework in the B2B space, ensuring European companies can capitalise on their strengths in industrial AI over the years ahead.
Industrial AI in action – delivering solutions to society’s big challenges
Thanks to recent technological advancements - in areas like computing power, advanced algorithms, and data transfer and storage - companies are developing and implementing new business models based on AI in areas such as healthcare, agriculture, energy, factory automation, smart cities and transport. Real-world use cases are demonstrating the potential of AI not only to enhance efficiency and productivity, but to respond to many societal challenges and contribute to sustainable development.
Here are some examples of how industrial AI can deliver benefits across sectors:
Circular economy
Waste management: AI-powered solutions can monitor waste streams and support autonomus sorting of recyclables
Energy technology
Affordable and clean energy for all: AI can optimise energy distribution infrastructure to support integration of renewables; make buildings more energy-efficient through smart sensor solutions; and boost efficiency of renewable power with predictive maintenance for wind turbines, for example.
Vibrant, liveable communities with net-zero carbon emissions: AI can help enable the intricate systems that will bring together renewable energy, new storage solutions, electric vehicles, smart buildings and similiar teach to enable net-zero emissions living.
Automation and manufacturing
Revolutionising global logistics and supply chains:
AI can be used to analyse and optimise shipping routes to reduce cost and enhance efficiency and sustainability.
Productivity gains, lower costs, high-quality products: AI technology can support manufactuting through predictive maintenance, industrial robotics to accelerate repetitive task, or digital twins that simulate real world operations to enable optimisation and test new business models.
Transport
Safe and secure autonomous driving:
AI-based machine learning is essential for autonomous driving in order to match human-level image recognition.
These examples show how Europe´s technology industries are taking an ethical, human-centric approach to leverage industrial AI as an engine for economic and societal progress.
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Wayback Machine: http://web.archive.org/web/20210510083701/https://orgalim.eu/news/orgalim-launches-technology-industries-manifesto-european-agenda-industrial-ai