The British government has frequently emphasized its goals of becoming an “AI superpower” in the world. Today, it revealed a new “AI rulebook” that it hopes would help regulate the industry, spur innovation, and increase public confidence in the technology. According to the AI rulebook, artificial intelligence regulation will be less centralized than it is in the EU and will instead give existing regulatory authorities the freedom to make choices based on the circumstances at hand.

AI rulebook seeks to support innovation

With the intention of giving regulators flexibility to implement these in ways that meet the usage of AI in particular industries, the UK’s approach is built on six basic principles that regulators must adhere to.

Damian Collins, the digital minister, provided a comment on the measures:

“We want to make sure the UK has the right rules to empower businesses and protect people as AI and the use of data keeps changing the ways we live and work.

It is vital that our rules offer clarity to businesses, confidence to investors and boost public trust. Our flexible approach will help us shape the future of AI and cement our global position as a science and tech superpower.”

At the moment, it might be challenging for businesses to navigate and comprehend the extent to which existing regulations apply to AI. The government is also worried that innovation may be impeded and that it will be more challenging for regulators to uphold public safety if AI legislation do not keep up with the rate of technological advancement.

The AI rulebook portrays artificial intelligence technology as a “general purpose technology,” similar to electricity or the internet, that will have a significant impact on many aspects of our life and vary significantly based on the context and application. Many of which, at this time, we probably even cannot predict.

According to the plans unveiled today, the UK’s approach to regulation appears to seek to give regulators and their industries as much latitude as possible. It remains to be seen if this gives organizations the clarity they require or not, but the expectation is that this strategy will provide them more investment freedom.

Contrary to the EU AI Act, which will be overseen by a single regulatory agency and seeks to standardize EU regulation across all member states, this AI rulebook is a different approach. The EU’s regulatory strategy is described in the rulebook as having a “relatively fixed definition in its legislative proposals.”

“Whilst such an approach can support efforts to harmonize rules across multiple countries, we do not believe this approach is right for the UK. We do not think that it captures the full application of AI and its regulatory implications. Our concern is that this lack of granularity could hinder innovation,” the AI rulebook states.

Instead, in what the UK refers to as a “Brexit seizing moment,” the AI rulebook outlines the fundamental aspects of artificial intelligence (AI) to help define the framework’s breadth while allowing regulators to develop more particular definitions of AI for their individual domains or industries.

“This is in line with the government’s view that we should regulate the use of AI rather than the technology itself – and a detailed universally applicable definition is therefore not needed. Rather, by setting out these core characteristics, developers and users can have greater certainty about scope and the nature of UK regulatory concerns while still enabling flexibility – recognising that AI may take forms we cannot easily define today – while still supporting coordination and coherence,” the AI rulebook adds.

In light of this, the AI rulebook suggests creating a “pro-innovation framework” for regulating artificial intelligence technologies. This framework would be supported by a set of principles that are:

• Context-specific: They suggest regulating AI in accordance with its application and the effects it has on people, communities, and enterprises within a specific environment, and giving regulators the task of creating and enacting suitable legislative responses. This strategy will encourage innovation.
• Pro-innovation and risk-based: They suggest concentrating on problems where there is demonstrable proof of actual risk or lost opportunities. And they want regulators to pay more attention to real threats than imagined or minor ones related to AI. They aim to promote innovation while avoiding erecting pointless obstacles in its path.
• Coherent: A set of cross-sectoral principles customized to the unique properties of AI are proposed, and regulators are requested to understand, prioritize, and apply these principles within their respective sectors and domains. They will search for ways to assist and encourage regulatory cooperation in order to create coherence and boost innovation by making the framework as simple to use as possible.
• Proportionate and adaptable: In order to make their approach adjustable, they want to first lay out the cross-sectoral ideas on a non-statutory basis, however they’ll keep this under review. They will request that regulators first take a light hand with options like voluntary actions or guidelines.

“We think this is preferable to a single framework with a fixed, central list of risks and mitigations. Such a framework applied across all sectors would limit the ability to respond in a proportionate manner by failing to allow for different levels of risk presented by seemingly similar applications of AI in different contexts.

This could lead to unnecessary regulation and stifle innovation. A fixed list of risks also could quickly become outdated and does not offer flexibility. 

A centralized approach would also not benefit from the expertise of our experienced regulators who are best placed to identify and respond to the emerging risks through the increased use of AI technologies within their domains,” the government stated. 

Cross-sectoral principles

The guideline acknowledges that the UK’s strategy does have risks and challenges. Compared to a centralized model, the context-driven approach delivers less uniformity, which could cause confusion and less assurance for enterprises. As a result, the UK wants to make sure that it handles “common cross-cutting challenges in a coherent and streamlined way” by adding a set of overarching principles to this strategy.

The cross-sectoral principles in the rules outline how the UK believes well-regulated AI use should behave and build on the OECD Principles on AI. Existing regulators will interpret and put the ideas into reality, and the government is looking into how it may strongly encourage the adoption of a “proportionate and risk-based approach.”

The AI rulebook summarizes cross-sectoral principle under 6 headlines:

• Ensure that AI is used safely
• Ensure that AI is technically secure and functions as designed
• Make sure that AI is appropriately transparent and explainable
• Embed considerations of fairness into AI
• Define legal persons’ responsibility for AI governance
• Clarify routes to redress or contestability

The principles will be put into practice by regulators, including Ofcom, the Competition and Markets Authority, the Information Commissioner’s Office, the Financial Conduct Authority, and the Medicine and Healthcare Products Regulatory Agency. They will be urged to take into account “lighter touch” methods, such as counseling, voluntary action, and setting up sandboxes.

Conclusion

In this case, the EU AI Act’s approach will probably have an impact on how AI regulation is handled globally, much like GDPR did. While context is crucial, there are numerous concerns linked with AI that might significantly affect people’s life. Flexibility is desirable, but the general public and consumers require clear channels for reporting or contesting the use of AI and access to information about the decision-making processes used. The UK clearly wants to adopt a hands-off strategy that encourages investment, but one must hope that this won’t come at the expense of decency, clarity, and equity.

The European Union is disturbed by the lack of comprehensive regulation of artificial intelligence. The EU AI Act is an important step that will determine the future of artificial intelligence in the context of personal data protection.

It’s a lawless world for artificial intelligence in today’s society. The European Union has a proposed solution called AI Act. Critical decisions about people’s lives are increasingly being made by AI programs without any regulation or accountability.

This can result in the imprisonment of innocent people, poor academic performance among students, and even financial crises. It is the first law in the world designed to regulate the entire sector and avert these harms. If EU succeeds, it could establish a new global standard for AI governance across the world.

What the EU AI Act proposes?

Here’s a brief summary of everything you need to know about the EU’s AI Act. Members of the European Parliament and EU member countries are currently amending the legislation.

The AI Act is very aggressive in its goals. It would need more checks on “high-risk” applications of AI, which have the most potential to cause damage to people. This might include systems for grading exams, recruiting workers, or assisting judges in making legal and judicial decisions. The bill’s first draft also contains restrictions on the use of AI deemed “unacceptable,” such as computing people’s trustworthiness based on their reputation.

The proposed legislation would also ban law enforcement agencies’ use of facial recognition in public spaces. There is a vocal group of influencers, including members of the European Parliament and nations like Germany, who want a total prohibition on its usage by both government and corporate bodies because they claim it allows for massive surveillance.

If the EU is able to execute this, it would be one of the most stringent bans yet on facial recognition technology. San Francisco and Virginia have imposed limits on facial recognition, but the EU’s prohibition would apply to 27 nations with a population of over 447 million people.

How EU AI Act will affect people?

By requiring that algorithms receive human review and approval, the bill should prevent humans from being harmed by AI in the event of an accident. According to Brando Benifei, an Italian member of the European Parliament who is a key player in preparing amendments for the bill, people may trust that they will be safeguarded from the most harmful forms of AI.

The AI Act also requires people to be notified if they encounter deepfakes, biometric recognition technologies, or AI applications that claim to be able to read emotions. Lawmakers are also discussing whether the legislation should include a system for individuals to file complaints and seek compensation if they have been damaged by an AI system.

One of the EU bodies working on amending the bill is also calling for a prohibition on predictive policing technologies. Predictive policing systems employ artificial intelligence to evaluate massive data sets in order to proactively deploy police to high-crime areas or try to forecast whether someone will become criminal. These algorithms are highly contentious, with critics alleging that they are frequently racial and lack transparency.

Are there any examples of such legislation outside of EU?

The GDPR, or the European Union’s data protection regulation, is one of the most well-known tech exports from the EU. It has been emulated in California to India. The EU’s approach to AI, which focuses on the riskiest AI, is a model that other advanced nations embrace. If Europeans can figure out how to regulate technology effectively, it might serve as a template for other countries wanting to do so as well.

“US companies, in their compliance with the EU AI Act, will also end up raising their standards for American consumers with regard to transparency and accountability,” explained Marc Rotenberg, the Center for AI and Digital Policy head.

The bill is also being watched closely by the Biden administration. The US is home to some of the world’s biggest AI labs, such as those at Google AI, Meta, and OpenAI, and leads multiple different global rankings in AI research, so the White House wants to know how any regulation might apply to these companies. For now, influential US government figures such as National Security Advisor Jake Sullivan, Secretary of Commerce Gina Raimondo, and Lynne Parker, who is leading the White House’s AI effort, have welcomed Europe’s effort to regulate AI. 

The debate over the EU AI Act is also being closely monitored by the Biden administration. The United States has several of the world’s largest AI laboratories, including those at Meya, OpenAI, and Google AI and it leads many different global rankings in AI research. As a result, the White House is seeking information on how any legislation would apply to these firms. For the time being, prominent government figures in Washington, such as National Security Advisor Jake Sullivan and Secretary of Commerce Gina Raimondo, have praised Europe’s efforts to regulate artificial intelligence.

“This is a sharp contrast to how the US viewed the development of GDPR, which at the time people in the US said would end the internet, eclipse the sun, and end life on the planet as we know it,” said Rotenberg.

Despite some unavoidable wariness, the United States has compelling reasons to embrace the bill. It is extremely concerned about China’s rising tech influence. According to Raimondo, for America, maintaining a Western edge in technology is still a question of “democratic values” prevailing. It wants to keep close ties with the EU, a “like-minded ally,” and prevent it from drifting away, Fedscoop reports.

What kind of obstacles are there?

Some of the requirements in the bill are physically impossible to fulfill right now. The bill’s initial draft stated that data sets should be free of errors and that humans should be able to completely comprehend how AI systems operate. If a human checked for completeness, it would take hundreds of hours to ensure that data sets are completely error-free. Even today’s neural networks are so complicated that their creators don’t know why they reach their judgments.

Regulators and external auditors are also wary of the mandates that tech businesses must implement in order to comply with legislation.

“The current drafting is creating a lot of discomfort because people feel that they actually can’t comply with the regulations as currently drafted,” says Miriam Vogel, The CEO of a nonprofit organization called EqualAI. She also heads the newly formed National AI Advisory Committee, which advises the White House on AI policy. There are also those saying that lawyers are at risk of losing their jobs to AI by 2030.

There’s also a heated debate going on about whether the AI Act should ban face recognition outright. It’s a contentious issue because EU nations dislike when Brussels tries to tell them how to handle national security and law enforcement issues.

In other countries, such as France, the government is considering special rules for the use of facial recognition to protect national security. In contrast, the new German government, another major European nation and an influential voice in EU decision making, has stated that it supports a total ban on face scanning in public places.

There will also be a debate about which types of AI should be labeled as “high risk.” The AI Act includes a variety of AI applications, such as lie detection tests and systems for allocating welfare payments. There are two competing political factions: one that fears that the broad scope of the legislation will stifle innovation, and another that claims that the bill does not go far enough to protect individuals from significant injury. Some consider facial recognition risky, is big data going too far?

What effect will the law have on technology development?

A frequent complaint from Silicon Valley lobbyists is that the new rules will add to the burden on AI firms. The EU disagrees. The European Commission, the EU’s executive body, argues that only the riskiest category of AI applications would be covered by the AI Act, which it predicts would apply to 5 to 15% of all AI apps. If you wonder how tech giants use artifical intelligence, learn how businesses utilize AI in security systems, here.

“Tech companies should be reassured that we want to give them a stable, clear, legally sound set of rules so that they can develop most of AI with very limited regulation,” explained Benifei. 

Organizations that do not comply with the AI Act will be fined up to $31 million (€30 million) or 6% of worldwide yearly sales. Europe has shown a propensity to hand out fines to tech businesses in the past. In 2021, Amazon was fined $775 million (€746 million) for failing to adhere to the GDPR, and Google was fined $4.5 billion (€4.3 billion) for violating EU antitrust regulations in 2018.

When will the EU AI Act come into effect? 

It will be at least another year before a final text is decided upon, and several years before firms must comply. There’s a chance that hammering out the fine points of such a comprehensive bill with so many contentious components may take longer than expected. The GDPR took more than four years to negotiate and six years to come into force in the EU. Anything is conceivable in the world of EU legislationmaking. If you are into artificial intelligence and ML systems, check out the history of Machine Learning, it dates back to the 17th century.

What is the future of AI in Europe and what does it take to build an AI solution that is attractive to investors and customers at the same time? How do we reimagine the battle of “AI vs Human Creativity” in Europe? 

Is there any company that is not using AI or isn’t AI-enabled in some way? Whether it is startups or corporates, it is no news that AI is boosting digital transformation across industries at a global level and hence it has traction not only from investors but is also the focus of government initiatives across countries. But where does Europe stand with the US and China in terms of digitization and how collective effort could push AI as an important pan-European strategic topic? 

First things first: According to McKinsey, the potential of Europe to deliver on AI and catch up against the most AI-ready countries such as the United States and emerging leaders like China is large. If Europe on average develops and diffuses AI according to its current assets and digital position relative to the world, it could add some €2.7 trillion, or 20 per cent, to its combined economic output by 2030. If Europe was to catch up with the US AI frontier, a total of €3.6 trillion could be added to collective GDP in this period.

What comprises the AI landscape and is it too crowded?

I recently attended a dedicated panel on “AI vs Human Creativity ” as a part of the first day of the Noah conference 2019 in Berlin.  Moderated by Pamela Spence, Partner, Global Life Sciences Industry leader, EY, the discussion started with an open question on whether the AI landscape is too crowded? According to a report by EY, there are currently 14000 startups globally which can be associated with the AI landscape. But what does this mean when it comes to the nature of these startups? 

 Minoo Zarbafi, VP Bertelsmann Investments Digital Partnerships, added perspective to these numbers,” There are companies that are AI-enabled and then there are so-called AI-first companies. I differentiate because there are almost no companies today that are not using AI in their processes. From an investor perspective, we at Bertelsmann like AI-first companies which are offering a B2B platform solution to an unsolved problem . For instance, we invested in China in two pioneer companies in the domain of computer vision that are offering a B2B solution for autonomous driving.” Minoo added that from a partnership perspective Bertelsmann looks at AI companies that can help on the digital transformation journey of the company. “The challenge is to find the right partner with the right approach for our use cases. And we actively seek the support of European and particularly German companies from the startup ecosystem when selecting our partners”, she pointed out. 

The McKinsey report too states that one positive point to note is that Europe may not need to compete head to head but rather in areas where it has an edge (such as in business-to-business [B2B] and advanced robotics) and continue to scale up one of the world’s largest bases of technology developers into a more connected Europe-wide web of AI-based innovation hubs.

Growing share of funding from Series A and beyond reflect increased maturity of the AI ecosystem in Europe. Pamela Spence from EY noted, “One in 12 startups uses AI as a part of their product or services, up from 50 about six years ago. Startups labelled as being in AI attract up to 50 per cent more funding than other technology firms. 40 per cent of European startups that are claimed as AI companies actually don’t use AI in a way that is material to their business.”

AI and human creativity go hand-in-hand

Another interesting and important question is how far are we from the paradigm of clever thinking machines? Why should we be afraid of machines?  Hans-Christian Boos, CEO & Founder, Arago compares how machines were earlier supposed to do tasks which are too tedious or expensive and complex for humans. “The principle of machine changes with AI. It used to earlier just automate tasks or standardise them. Now, all you need is to describe what you want as an outcome and the machine will find that outcome for you- that is a different ballgame altogether. Everything is result-oriented,” he says.

Minoo Zarbafi adds that as human beings, we have a limited capacity for processing information. “With the help of AI, you can now digest much more information which may cause you to find innovative solutions that you could not see before. One could say, the more complexity, the better the execution with AI. At Bertelsmann, our organisation is decentralised and it will be interesting to see how AI leverages operational execution.”  

AI and the Political Landscape

Why discuss AI when we talk about the digital revolution in Europe? According to the tech.eu report titled ‘Seed the Future:  A Deep Dive into European Early-Stage Tech Startup Activity’, it would be safe to say that Artificial Intelligence, Machine Learning and Blockchain lead the way in Europe. The European Commission has identified Artificial Intelligence as an area of strategic importance for the digital economy, citing it’s cross-cutting applications to robotics, cognitive systems and big data analytics. In an effort to support this, the Commission’s Horizon 2020 funding includes considerable funding AI, allocating €700M EU funding specifically.

Chiara Sommer, Investment Director, Intel Capital reflected on this by saying, “In the present scenario, the implementation of AI starts with workforce automation with a focus on how companies could reduce cost and become more efficient. The second generation of AI companies focuses on how products can offer solutions and solve problems like never before. There are entire departments can be replaced by AI. Having said that, the IT industry adopts AI fastest, and then you have industries like healthcare, retail, a financial sector that follow.” 

Why are some companies absorbing AI technologies while most others are not? Among the factors that stand out are their existing digital tools and capabilities and whether their workforce has the right skills to interact with AI and machines. Only 23 percent of European firms report that AI diffusion is independent of both previous digital technologies and the capabilities required to operate with those digital technologies; 64 percent report that AI adoption must be tied to digital capabilities, and 58 percent to digital tools. McKinsey reports that the two biggest barriers to AI adoption in European companies are linked to having the right workforce in place.

It is certainly a collective effort of industries, the government, policy makers, corporates to have effective and impactful use of AI. Instead of asking how AI will change society Hans-Christian Boos rightly concludes, “We should change the society to change AI.”

Note: The quotes used in this article are derived from a panel discussion at NOAH Conference Berlin 2019.

Here is what “The State of European Tech 2018”, a data-driven analytical report by Atomico reveals about the factors that are accelerating the growth of tech in the European economy

The comparison of Europe’s tech scene with Silicon Valley in the U.S and Asia (particularly China) has been a topic of debate for long criticising not only the lack of consumer-tech companies in EU, but also the mere lack of tech innovation supported by EU policies.  

Amidst this cynicism, there are numbers which tell a story of constant progress in the European tech economy and break many myths of the past. Lack of VC funding is not a problem anymore and tech workforce in EU is on the rise. The State of European Tech 2018, a data-driven analytical report by Atomico states that while Europe’s overall economy and traditional industries are stuck in the doldrums, booming tech represents the best hope for growth. Tech firms are powering job creation and ambitious founders are tackling some of the world’s biggest problems. All of that has members of the ecosystem optimistic – except in the U.K. where sentiment is not at the same levels as elsewhere.

Some of the key findings of the report mention:

• The amount invested in Europe’s technology ecosystem is $23bn in 2018, up from just $5bn in 2013.
• There were four tech IPOs or direct listings of European tech companies in 2018 that reached valuations of more than $5B on opening day, including Europe’s largest ever venture-backed publicly-listed tech company, Spotify.
• In total, Europe contributed three of the top 10 largest tech IPOs globally of 2018.

Chris Grew, Partner, Technology Companies, Group Orrick says, “There has been a nearly five-fold growth in European venture capital investment in the last five years. There are five times the number of unicorns – with at least 17 new billion dollar plus companies added in the past year alone. The European tech sector has produced nearly four times the job growth rate of the general economy, resulting in a talent pool of programmers and STEM researchers surpassing that of the United States. At Orrick, we see it in our practice every day as we have helped founders, investors and corporate venture clients raise or deploy more than $3.7 billion across Europe over the past year.” He mentions that as a global tech law firm, they are not surprised to see investors from around the world chasing strong returns from their European investments. While U.S. investment returned to 2016 levels after another record-breaking performance last year, investment from Asia continued to grow.

Here are the factors (according to the report) driving this high growth for European tech:

Powering Workforce Growth

Tom Wehmeier, Partner, Atomico says, “Last year we found that Europe was experiencing a ‘Battle Royale’ for talent. This year was the year Europe figured out how to effectively mobilise its deep pools of talent. The tech sector is attracting more participants – whether measured by the healthy increase in professional developers or the uptick in talented executives moving into tech from other sectors. What is interesting is that the developer pool is growing fastest outside those countries that have historically attracted the most investment: Turkey, Spain and Russia’s pool of developers have been deepening the most rapidly. All this will lead to a massive potential upside for the wider European economy as capital eventually grows into these new communities,” he says.

Employment growth in the European economy as a whole is stalling. The European Commission’s latest forecast for 2018 employment growth implies a drop to just 1.1% year-on-year growth, a material decline from the level seen in 2017. On the other hand, Europe’s tech workforce grew 4% in 2018. It is worth comparing the EU employment growth rate to the remarkable worker population growth that powers the European tech industry.

Within Europe, the French tech worker population is growing significantly faster than Germany and UK. The rate of tech workforce across Europe is not equally distributed, with workforces in some growing much faster than others. France, for example, hit 7.3% growth in 2018, making it comfortably the fastest growing tech workforce in EU.

Tech: The Motor for GDP Growth

There is an ever-widening gap in the indexed growth rates of the tech (software) and non-tech parts of the European economy. The implication of this sustained difference in growth rates is starkly visible when looking at indexed growth of the tech parts of the European economy. Over the past 15 years, tech (software) has grown to hit 194% of its relative value in 2002. Europe’s software industry growth dramatically outpaces the rest of the European economy.

Today, the European tech (software) industry is now growing 5x faster than the rest of the economy. Over the last 10 years, many of these traditional industries upon which the European economy is so dependent have either stagnated or declined, undermining the overall rate of growth in European Gross Value Added.

The European tech (software) industry contributes around $400 billion to the European economy today, remains just a fraction of total European Gross Value Added, accounting for just 2.5 % of total European GVA.

Smiles (almost) all round in European tech

Europe’s tech ecosystem remains characterised by a strong level of growing optimism about the future.  This increase in optimism is most evident in Eastern and Southern Europe

where there is real momentum. The UK, perhaps unsurprisingly, registered the largest downturn in optimism by a wide downturn in optimism by a wide margin. There continues to be a very strong sense of optimism across the European tech ecosystem

90 per cent of the European tech community is either more optimistic about the future of European tech or maintain the same levels of optimism compared to 12 months ago. This remains the same as in 2017 when 91% of respondents were more optimistic or the same.

“ I’m definitely more optimistic than 12 months ago. I think we’re seeing a marked shift in ambition in Europe, and crucially, that’s being matched at an investor level. What’s more, the increased cost of living and hiring competition seems to have taken the blinkers off a lot of Valley-bound entrepreneurs. This can only benefit Europe.” says Rosie Dallas, Fat Llama.

Tech for Good: A European Opportunity?

There is strong agreement across all stakeholders, including within the public sector, that European tech entrepreneurs will have a bigger impact than European governments when it comes to solving important global challenges.  64 % of the public sector and policymaker respondents who agree that European technology entrepreneurs will do more to address major societal challenges than European governments.

“ Compared to the US, we seem to be a bit further ahead when it comes to sustainability. Especially when it comes to food waste and climate consciousness, both among consumers and within the food industry..Compare this with President Trump’s decision to withdraw from the Paris agreement a year ago…One thing that has influenced us at Karma is that we’ve had mission-driven, competent and successful entrepreneurs, such as Niklas Adalberth founding Norrsken Foundation, drive the agenda of using entrepreneurship to build technologies that can solve social challenges on a global scale,” says Elsa Bernadotte from Karma.

Final Thoughts

Tom Wehmeier, Partner, Atomico leaves us with a word to the naysayers and critics of European tech: irrespective of the huge strides European tech has taken in the last few years, our tech sector will continue to be compared to the performance of Silicon Valley. ”For a long time, US VC has outperformed European VC in terms of portfolio returns, but that is increasingly untrue. The latest historical performance data shows that European venture has been outperforming US venture in recent horizon periods. We believe this is a bellwether for a changing landscape. Let’s not forget that 95% of the value creation of today’s US tech sector is from companies founded 15 years ago or more and that the early tech successes of ARM, Amadeus and Ocado were not venture-backed. Given that 21 European companies have been founded and scaled to billion-dollar-plus valuations with the support of venture capital since 2010 alone, we are confident that Europe has caught up on North America’s head start, “ he concludes.

Disclaimer: The content of this article is based on a section of The State of European Tech report. The full report can be downloaded here.

The Ruhr region known to be a steel and coal mine hub in Europe is reimagining the entrepreneurial spirit which was it’s foundation 150 to 200 years ago. This time lies a huge opportunity for data-driven startups to innovate and collaborate with the big traditional corporates that exist in the region. Here is look how.  

The year 2018 is a significant one for the Ruhr region in Europe. At the end of this year, Prosper-Haniel mine in Bottrop, the last coal mine in the region will be closed. Decisions which were made more than a decade ago are now reaching its inflexion point. To refresh the memory : In February 2007, the German federal government, the NRW (North Rhine-Westphalia) and Saarland State governments (where hard coal mining still took place), and RAG, the coal mine company owning and operating all of the Ruhr’s coal mines since 1969, reached an agreement on the final phasing out of underground coal mining in Germany and its subsidies by 2018. Over the last 50 to 60 years, there has been an economic transition from a steel and coal based economy in Ruhr to a serviced economy which now has huge potential for smart manufacturing and internet of things. This has lead to discussions whether Ruhr area could be the new hot spot for startups and tech innovation? The region is one of the five largest conurbations in Europe and is home to approximately 5.2 million people.

Whenever there are significant changes like these, there are also immense opportunities. While this is an end of an era of coal mines, it is a birth of a new one. When we ask Marc Weimer-Hablitzel, Lead, Data Hub, Gründerallianz Ruhr about what this will change for existing big companies in Ruhr and what opportunity lies ahead for startups in the region, he says, “ If you look at data science from the perspective of B2B traditional companies, they are just starting to understand that data is not just a technical topic- rather it is their main source for competitive advantage which further leads to revenue generation. They realise that there is huge potential if you apply machine learning in processes like quality measures, energy consumption, etc. This industrial revolution in Ruhr region emphasises on the role of companies to care more about reducing pollution and saving energy. The right use of data by these traditional huge corporates can solve the problem. ”

Germany has a target of reducing greenhouse gas emissions by 55 per cent by 2030 compared to the 1990s levels, and data-driven solutions can help in a big way to achieve this goal. And, startups are the ones who are innovating constantly to come up with these solutions. What is missing is a framework where startups can connect to these giant companies who have existed for years.

Catering to this, Gründerallianz Ruhr supports the innovation ecosystem in the Ruhr region in Germany and bundles all startups activities in the area. The goal of this initiative is to strengthen the local startup scene and nourish it’s growth.  Gründerallianz Ruhr was founded by Initiativkreis Ruhr and the initiators of „Glückauf Zukunft!“, RAG-Stiftung, RAG Aktiengesellschaft and Evonik Industries.

What problem can startups solve in the Ruhr region and how?

Marc draws an interesting analogy between how the Ruhr region started with an entrepreneurial and startup mindset around 150 to 200 years ago when people were driven to build a steel and coal based economy from the region of Ruhr to now when the same mindset will bring the next wave of change in the region through data-driven solutions.

He says, “We want to bring out the same attitude of innovation but in a way where data science and machine learning is being adopted by traditional B2B companies. We want to make the Ruhrgebiet an attractive location for data-driven startups .”  The Data Hub Program by Gründerallianz Ruhr creates the framework conditions and promotes cooperation between startups and companies based on concrete use cases.

A whitepaper by The World Economic Forum says that while the European economy is growing faster than the US economy at present, the European innovation ecosystem is stronger than ever before but still trails other markets in terms of available nance and collaboration. The European economy’s continued success requires a better connection between both worlds: the traditional businesses and new market players. Both benefit from collaboration to create markets they would struggle to create alone, and to ensure they remain at their competitive edge. This exactly resonates with the mission of what Data Hub Program is trying to do by connecting startups with big corporates.

The program is now inviting startup applications to solve challenges/use cases listed by top corporates such as Vivawest, Kolumbus and RAG in Ruhr Region and Gründerallianz Ruhr is the glue between these alliances of startups and companies. Marc shares, “ We are the facilitators between the two. This is a time when companies feel that they should be using data-driven solutions and they are beginning to share information with the outside world. For the last 15 years,  data has been a CTO topic and it was hard to imagine that it could have some return on investments or be monetised. It was collected and stored as a practice, but without a purpose. CEOs have now started realising that good customer experience comes from developing data in the most efficient manner. In a recent etventure study, we asked CEOs what’s the most important source for competitive advantage and 63 percent of them answered it was “data”. This was not the case five years ago.”

The challenge right now is that while corporates have huge amounts of data and though they also have data scientists employed, these scientists end up working in silos struggling how to use heaps of data, not being able to differentiate between good data and bad data. On the other hand, there are young startups who have data sets and don’t know how to use them as they don’t know which are the use cases available by big companies.  

“We are the point to bring these two sides together and reduce friction that is hindering them to work together.  The legal work to collaborate with a big company could be a lot for a startup and we take care of these necessary logistics. In return,  we expect startups to deliver a solution that gives a corporate enough confidence that they can solve the problem overcoming the first hurdle by developing a proof of concept,” shares Marc.

What are the use cases and how are they developed?

One of the use cases that is open for startup applications at this point is listed by RAG, one of the ten partners of Gründerallianz Ruhr.

Sample this from the perspective of RAG: The last two RAG mines will close at the end of 2018. As a result, the challenges of post-mining and structural change will become the focus of our activities starting in 2019. We are already setting the course today – for example with a variety of measures for socially responsible personnel adjustment, the planning and implementation of responsible water management or the revitalization of former mining areas.

To help keep the Ruhr area safe, RAG conducts flights that measure exact ground elevation levels. These measurements reveal ground depressions that can be used in the future. Spotting these depressions is a difficult task. Can we develop an algorithm that spots ground depressions better than the human eye? There are similar challenges by a total of seven big global companies based in Germany at present and startups can apply by 31st October in an attempt to solve these use cases.

Marc explains the unique data thinking approach which is used to develop these use cases, “ Data Thinking is a new innovation method that moves away from traditional big data consulting. The focus is not on technology and data collection, but on data design for high-potential use cases. In the systematic identification of these data use cases, the data thinking method follows that of design thinking – placing the needs of the customer or user at the center of all considerations. Data Thinking is a highly iterative and cost-effective data science approach that demands fast feedback directly from the user and continuously tests, analyzes and optimizes potential solutions and hypotheses.”

With the right financing for startups and a framework where big corporates can collaborate with younger innovative companies- there possibly is a big industrial revolution waiting yet again for Ruhr region. This time backed by the adoption of machine learning and data science.

In politics decision making takes time, especially when there is a lot at stake. In Brussels, home of the European Union, this has been the case for the new EU data protection package.

Last June, the EU Civil Liberties and Justice Committee (aka LIBE) entered “trilogue” negotiations between the EU Parliament (representing us, the citizens), the EU Commission (the government of the EU) and the EU Council (all 28 heads of EU member states’ governments) on the proposed changes in Data Protection regulations. On the 17th of December 2015 LIBE announced that all parties have finally reached agreement consensus.

The major points of the package are:

• Explicit consent: Companies that want to use personal data for purposes other than delivering the service for which their clients provide the data, must seek formal, written permission from the client for such use. No more “general data processing” tick boxes. Instead, companies will need “explicit consent.”
• Right to be forgotten: In some instances, like when the data has been collected during a time when the data subject was a minor and in need of parental consent, data subjects have a “right to be forgotten.” Their personal data must be removed from IT systems, including those in test environments.
• Privacy by design: All IT systems must be “privacy ready.” Data protection must be by design, not as an afterthought.
• Onerous fines: Failure to comply will be met with massive fines, up to 4 percent of the offender’s global turnover. For large global companies, this could amount to billions.
• Timeframe: Upon enactment, companies will have two years to adopt.

As the LIBE rapporteur, Jan Albrecht put it, “The regulation returns control over citizens’ personal data to citizens. Companies will not be allowed to divulge information that they have received for a particular purpose without the permission of the person concerned. Consumers will have to give their explicit consent to the use of their data.”

How easy is it to ‘forget’?

The new rules coming into force with the arrival of the EU Data Regulations pose a major challenge for all companies that collect and store personal data. Take for example the “Right to be forgotten.” To be able to execute on this law it requires companies to be in control of where any personally identifiable information (PII) resides within their systems. This might sound pretty simple, but it’s far from it; organisations not only need to consider their own back-end databases and backups, but they also need to consider any data being used by outsourcers, partners or cloud service providers they’re working with. In many cases, data could even be in use outside of the EU—in the systems of an outsourcer developing mainframe applications for the business, for example. This would instantly create a breach of the new EU regulations unless the proper controls were in place.

we consent to having our data used for system testing?

Explicit consent seems simple. We all know the tick boxes that we already see when doing business online. But do we ever read and understand what our data is collected and used for? What data do these online services need to deliver the service request and what kind of data is collected that has ‘purposes other than delivering the service for which the clients provide the data”? Do we consent to the latter?

Translating this issue from legal into IT lingo, we can take testing as an example: testing applications with real personal data will require an explicit consent of the end customer. If customers were to reject to the usage of their data in testing it could severely impact application testing. Complex applications, such as those developed for the mainframe, are often tested using live customer data in order to create an impression of how they’ll perform in the real world. However, this practice is already unlawful when businesses have not treated the data as personal and put stringent controls in place, not to mention informing people what their data will be used for beyond “normal business.” This is even more significant when the data is being used by third-parties, such as outsourcers. Unless the business has explicit consent from the customer for their data to be handed to an outsourcer and used in controlled testing environments, they’ll be in direct breach of the new EU legislations and face a painful fine.

Impact on testing/development

Alarmingly, research by Compuware indicates that many businesses lack a clear understanding of how their testing practices will be impacted by the new data protection legislation. A fifth of firms do not mask or protect customer data before sharing it with outsourcers, with the vast majority of them relying on non-disclosure agreements that in essence do not satisfy even current data privacy regulation. It is therefore extremely important for all businesses to start looking at their testing practices to ensure that they can comply with the “privacy by design” demand of the EU laws.

If any real personal data is used for testing, it’s high time to start protecting it with a test data privacy project to ensure compliance with the existing as well as new EU regulations. There is absolutely no excuse for continuing to use unmasked customer data in testing projects, and those that continue to do so will have nowhere left to hide when the EU legislators come calling.

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