Although artificial intelligence (AI) promises greater efficiency and could provide the key to tackling some of society’s most pressing issues, not all Europeans are welcoming the technology with open arms.
In a newly published thought leadership paper from SAP entitled “European Prosperity Through Human-Centric Artificial Intelligence,” prepared by Andreas Tegge, head Global Public Policy, SAP addresses some anxieties and proposes measures for ensuring AI’s rapid assimilation and advancement in Europe.
It is probably fair to say that no other technology currently inspires such fascination nor stirs up such heated debate as AI and the branch of AI known as machine learning. Algorithms that are capable of autonomously gaining insight from data without being explicitly programmed are already empowering machines to see, read, listen, and interact. In the intelligent enterprise, machine learning allows better and more efficient processes, which means that enterprises benefit from increased productivity levels and employees have more time to devote to tasks that add greater value.
Machine learning will one day have applications in almost every branch and sector of industry. As far as the business benefits go, there’s more to machine learning than just saving money: It enables companies to make predictions about markets, customer behavior, and the service life of machinery; it vastly improves a company’s operations; and it allows fully personalized customer services and software use. What’s more, machine learning can also help tackle some of today’s most pressing social challenges — in health, disaster prevention, public safety, and so on.
Yet at the same time, anxieties and uncertainties about machine learning abound. What impact will machine learning have on the job market? How can we ensure data privacy and maintain human control over machine-driven decision-making processes? Will machines soon be a match for human intelligence? Or even outstrip it?
Luka Mucic, chief financial officer and member of the Executive Board of SAP SE, says it is important to address these concerns and insecurities in a public discussion: “People will play the most important role in the future as well, but that role will change. The goal should be for man and machine to complement each other in the workplace, with machines supporting human work. To be prepared, politics, industries, and civil society must engage in a multi-stakeholder dialogue. SAP hopes to contribute to the discussion with this thought leadership paper.”
Europe’s Opportunity on the Global Market
There is no doubt that AI will be a key driver of innovation, growth, and productivity in the future. But what will Europe’s role be? As things stand, the race for global dominance in AI is between China and the United States, with Europe ‒ so far at least ‒ seemingly doing little more than watch from the sidelines.
The United States is currently ahead. Companies like Google, Facebook, and Microsoft are investing in machine learning technologies but they are also at an advantage from having access to vast amounts of data. In 2016, the United States accounted for almost two-thirds of all the investments made in machine learning technologies.
For its part, China benefits from a formidable talent pool and the data gold mine generated by its 1.4 billion population. And it is ready to take on a global leadership role in AI alongside the United States. The Chinese government recently set out a development plan aimed at securing global market leadership in AI for China by 2030. Enterprises like Alibaba and Baidu are investing heavily in self-driving vehicles, smart traffic, defense, and health. And it is estimated that the Chinese market for AI could hit €5 billion by the end of 2018.
Consequently, you could be forgiven for thinking that Europe is out of the running. But, when it comes to the B2B market for AI and the intelligent enterprise, Europe has what it takes to play a leading role. Intelligent business processes, intelligent infrastructures, digital assistants, and chatbots are a rich source of opportunities for the application of machine learning.
Europe also has impressive industry expertise, which is vital for developing state-of-the-art machine learning solutions. Many European enterprises, both large and small, are world leaders in their fields and have tremendous innovative potential. There are startup hubs in Paris, London, and Berlin focusing intensively on AI. As far as data analytics is concerned, European companies are already well positioned with machine learning solutions.
Nevertheless, Europe faces some very particular challenges when it comes to society’s acceptance of machine learning technologies. Machine learning will only be successful in Europe if its development and application respect legal standards and European values.
Welcome to the “Dark Factory”?
The future of work will be impacted by the degree to which machine learning touches the various facets of an enterprise. It is taken as read that machine learning will open up potential for workplace automation in many areas. But experts disagree when it comes to defining which jobs will be affected by automation and what the scale of that impact will be. Estimates put the share of all workplace activities affected anywhere between five and 47 percent.
However, machine learning will create jobs too, not least because we will need specialists to develop machine learning systems and operate them efficiently. To say nothing of the fact that human originality, creativity, and innovation will be more in demand than ever before, which means we will see completely new jobs evolving. Machine learning could also counter the effects of the labor bottleneck Europe is currently facing as a result of demographic change and relieve companies of the pressure to relocate their production to low-wage countries.
It is difficult to predict what the precise effects will be, but AI will probably be evolutionary rather than revolutionary. “Most of these developments await us some time in the future and go well beyond what is possible in machine learning today,” says Markus Noga, head of the Machine Learning team at SAP. “We’re holding the reins and we can play an active part in shaping what is automated and to what extent. At the end of the day, our objective is to enhance human potential through technology, not to hinder it.”
SAP Chief Innovation Officer Jürgen Müller thinks that the “dark factory,” which operates with the lights switched off because machines don’t need light, is an unrealistic scenario: “Machine learning can automate very specific tasks, but AI is still far from being as multi-faceted as humans are, and may never even reach that stage. The future of work will be defined primarily by the interaction between humans and machines. It is therefore crucial that humans use AI to complement and enhance their own abilities rather than trying to compete with it.”
What Course Must We Set? What Does SAP Recommend?
To remain competitive, Europe needs to take advantage of the rich opportunities offered by the B2B market. That involves addressing legitimate concerns. The thought leadership paper from SAP makes specific recommendations for European governments and businesses about how they can join forces to accelerate the adoption and advancement of AI technologies in Europe.
In this regard, it is important that a social dialog begins between all the relevant stakeholders ‒ from politics, business, and society ‒ both within the individual member states of the European Union and at EU level, too, so as to develop a joint vision for AI in Europe.
SAP is in favor of a uniform legal framework within the EU that advances the development of AI and promotes large-scale research and innovation clusters. This would form the basis for collaboration and the use of large datasets to make machine learning models more robust and reliable, and for research projects into the future of work.
Promoting machine learning-relevant skills and abilities in the workforce is also a top priority. This means not only that the career starters of the future must be readied for tasks in an AI-based environment, but that industry as a whole must make sure that today’s workforces receive the additional training and qualifications they need.
Of paramount importance to the development of future machine learning solutions is the availability of training data for machine learning. Consequently, SAP calls for a loosening ‒ within the boundaries of existing data protection requirements ‒ of technical and administrative obstacles to allow the use of data via, for example, the European Data Portal for public administration data.
SAP also proposes drawing up a code of conduct for good AI governance and business practices, in which the industry agrees to adhere to basic principles and specific procedures in order to safeguard ethical and legal standards in the development and use of machine learning solutions.
SAP also sees Europe’s public sector as having a responsibility to become a forerunner in the use of AI to make its benefits tangible for citizens and to establish a broader understanding of what AI can do. The same applies to the small and midsize enterprise (SME) sector, the backbone of Europe’s economy. The adoption of AI in this sector represents a huge opportunity to speed up the digital transformation in small and midsize enterprises.
“Human beings must be at the center of any discussion about artificial intelligence,” said Bernd Leukert, member of the Executive Board of SAP SE, Products & Innovation. “To both address people’s concerns and take advantage of the economic opportunities, it is important for Europe to find its own path when it comes to the development and use of artificial intelligence. The tech industry must foster trust in these technologies. At SAP, we want to take a leadership role here.”
For more information about SAP’s stance on AI and machine learning, see the thought leadership paper.