Now the outlines for the AI Act are known, a debate is beginning to erupt around its possible implications. One camp believes regulations are needed to curb the risks of powerful AI technology, while the other is convinced that regulation will prove pernicious for the European economy. Is it out of the question that safe AI products also bring economic prosperity?

‘Industrial revolution’ without Europe

The EU “prevents the industrial revolution from happening” and portrays itself as “no part of the future world,” Joe Lonsdale told Bloomberg. He regularly appears in the US media around AI topics as an outspoken advocate of the technology. According to him, the technology has the potential to cause a third industrial revolution, and every company should already have implemented it in its organization.

He earned a bachelor’s degree in computer science in 2003. Meanwhile, he co-founded several technology companies, including those that deploy artificial intelligence. He later grew to become a businessman and venture capitalist.

The only question is, are the concerns well-founded? At the very least, caution seems necessary to avoid seeing major AI products disappear from Europe. Sam Altman, a better-known IT figure as CEO of OpenAI, previously spoke out about the possible disappearance of AI companies from Europe if the rules become too hard to apply. He does not plan to pull ChatGPT out of Europe because of the AI law, but he warns here of the possible actions of other companies.

ChatGPT stays

The CEO himself is essentially a strong supporter of security legislation for AI. He advocates for clear security requirements that AI developers must meet before the official release of a new product.

When a major player in the AI field calls for regulation of the technology he is working with, perhaps we as Europe should listen. That is what is happening with the AI Act, through which the EU is trying to be the first in the world to put out a set of rules for artificial intelligence. The EU is a pioneer, but it will also have to discover the pitfalls of a policy in the absence of a working example in the world.

The rules will be continuously tested until they officially come into effect in 2025 by experts who publicly give their opinions on the law. A public testing period which AI developers should also find important, Altman said. The European Union also avoids making up rules from higher up for a field it doesn’t know much about itself. The legislation will come bottom-up by involving companies and developers already actively engaged in AI setting the standards.

Copy off

Although the EU often pronounces that the AI law will be the world’s first regulation of artificial intelligence, other places are tinkering with a legal framework just as much. The United Kingdom, for example, is eager to embrace the technology but also wants certainty about its security. To that end, it immerses itself in the technology and gains early access to DeepMind, OpenAI and Anthropic’s models for research purposes.

However, Britain has no plans to punish companies that do not comply. The country limits itself to a framework of five principles that artificial intelligence should comply with. The choice seems to play to the disadvantage of guaranteed safety of AI products, as the country says it is necessary not to make a mandatory political framework for companies, to attract investment from AI companies in the UK. So secure AI products and economic prosperity do not appear to fit well together according to the country. Wait and see if Europe’s AI law validates that.

(Editor’s note: This article first appeared on Techzine)

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Authors: Sean Musch, AI & Partners and Michael Borrelli, AI & Partners

AI – The opportunity and the challenge

AI currently delivers broad societal benefits, from medical advances to mitigating climate change. As an example, an AI technology developed by DeepMind, a UK- based business, can predict the structure of almost every protein known to science. Government frameworks consider the role of regulation in creating the environment for AI to flourish. AI technologies have not yet reached their full potential. Under the right conditions, AI will transform all areas of life and stimulate economies by unleashing innovation and driving productivity, creating new jobs and improving the workplace.

The UK has indicated a requirement to act quickly to continue to lead the international conversation on AI governance and demonstrate the value of our pragmatic, proportionate regulatory approach. In their report, the UK government identify the short time frame for intervention to provide a clear, pro-innovation regulatory environment in order to make the UK one of the top places in the world to build foundational AI companies. Not too dissimilar to this EU legislators have signalled an intention to make the EU a global hub for AI innovation. On both fronts responding to risk and building public trust are important drivers for regulation. Yet, clear and consistent regulation can also support business investment and build confidence in innovation.

What remains critical for the industry is winning and retaining consumer trust, which is key to the success of innovation economies. Neither the EU nor the UK can afford not to have clear, proportionate approaches to regulation that enable the responsible application of  AI to flourish. Without such consideration, they risk creating cumbersome rules applying to all AI technologies.

What are the policy objectives and intended effects?

Similarities exist in terms of the overall aims. As shown in the table below, the core similarities revolve around growth, safety and economic prosperity:

What are the problems being tackled?

Again, similarities exist in terms of a common focus: the end-user. AI’s involvement in multiple activities of the economy, whether this be from simple chatbots to biometric identification, inevitably mean that end-users end up being affected. Protecting them at all costs seems to be the presiding theme:

What are the differences in policy options?

A variety of options have been considered by the respective policymakers. On the face of it, pro-innovation requires a holistic examination to account for the variety of challenges new ways of working generate. The EU sets the standard with Option 3:

What are the estimated direct compliance costs to firms?

Both the UK Approach and the EU AI Act regulatory framework will apply to all AI systems being designed or developed, made available or otherwise being used in the EU/UK, whether they are developed in the EU/UK or abroad. Both businesses that develop and deploy AI, “AI businesses”, and businesses that use AI, “AI adopting businesses”, are in the scope of the framework. These two types of firms have different expected costs per business under the respective frameworks.

UK Approach: Key assumptions for AI system costs

Key finding: Cost of compliance for HRS highest under Option 3

EU AI Act: Total compliance cost of the five requirements for each AI product

Key finding: Information provision represents the highest cost incurred by firms.

In light of these comparisons, it appears the EU estimates a lower cost of compliance compared to the UK. Lower costs don’t confer a less rigid approach. Rather, they indicate an itemised approach to cost estimation as well as using a standard pricing metric, hours. In practice, firms are likely to aim to make this more efficient by reducing the number of hours required to achieve compliance.

Lessons from the UK Approach for the EU AI Act

The forthcoming EU AI Act is set to place the EU at the global forefront of regulating this emerging technology. Accordingly, models for the governance and mitigation of AI risk from outside the region can still provide insightful lessons for EU decision-makers to learn and issues to account for before the EU AI Act is passed.

This is certainly applicable to Article 9 of the EU AI Act, which requires developers to establish, implement, document, and maintain risk management systems for high-risk AI systems. There are three key ideas for EU decision-makers to consider from the UK Approach.

AI assurance techniques and technical standards

Unlike Article 17 of the EU AI Act, the quality management system put in place by providers of high-risk AI systems is designed to ensure compliance. To do this, providers of high-risk  AI  systems must establish techniques, procedures, and systematic actions to be used for development, quality control, and quality assurance. The EU AI Act only briefly covers the concept of assurance, but it could benefit from publishing assurance techniques and technical standards that play a critical role in enabling the responsible adoption of AI so that potential harms at all levels of society are identified and documented.

To assure AI systems effectively, the UK government is calling for a toolbox of assurance techniques to measure, evaluate, and communicate the trustworthiness of AI systems across the development and deployment life cycle. These techniques include impact assessment, audit, and performance testing along with formal verification methods. To help innovators understand how AI assurance techniques can support wider AI governance, the government launched a ‘Portfolio of AI Assurance techniques’ in Spring 2023. This is an industry collaboration to showcase how these tools are already being applied by businesses to real-world use cases and how they align with the AI regulatory principles.

Similarly, assurance techniques need to be underpinned by available technical standards, which provide a common understanding across assurance providers. Technical standards and assurance techniques will also enable organisations to demonstrate that their systems are in line with the regulatory principles enshrined under the EU AI Act and the UK Approach. Similarities exist in terms of the stage of development.

Specifically, the EU AI Act defines common mandatory requirements applicable to the design and development of certain AI systems before they are placed on the market that will be further operationalised through harmonised technical standards. In equal fashion, the UK government intends to have a leading role in the development of international technical standards, working with industry, international and UK partners. The UK government plans to continue to support the role of technical standards in complementing our approach to AI regulation, including through the UK AI Standards Hub. These technical standards may demonstrate firms’ compliance with the EU AI Act.

A harmonised vocabulary

All relevant parties would benefit from reaching a consensus on the definitions of key terms related to the foundations of AI regulation. While the EU AI Act and the UK Approach are either under development or in the incubation stage, decision-makers for both initiatives should seize the opportunity to develop a shared understanding of core AI ideas, principles, and concepts, and codify these into a harmonised transatlantic vocabulary. As shown below, identification of where both initiatives are in agreement, and where they diverge, has been undertaken:

How AI & Partners can help

We can help you start assessing your AI systems using recognised metrics ahead of the expected changes brought about by the EU AI Act. Our leading practice is geared towards helping you identify, design, and implement appropriate metrics for your assessments.

 Website: https://www.ai-and-partners.com/

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The AI Act, set to be a global precedent, aims to address the risks associated with AI while encouraging the development of cutting-edge technology. One of the key aspects of this Act is its support for open-source, non-profit, and academic research and development in the AI ecosystem. Such support ensures the development of safe, transparent, and accountable AI systems that benefit all EU citizens.

Drawing from the success of open-source software development, policymakers can craft regulations that encourage open AI development while safeguarding user interests. By providing exemptions and proportional requirements for open ML systems, the EU can foster innovation and competition in the AI market while maintaining a thriving open-source ecosystem.

Representing both commercial and nonprofit stakeholders, several organisations – including GitHub, Hugging Face, EleutherAI, Creative Commons, and more – have banded together to release a policy paper calling on EU policymakers to protect open-source innovation.

The organisations have five proposals:

1. Define AI components clearly: Clear definitions of AI components will help stakeholders understand their roles and responsibilities, facilitating collaboration and innovation in the open ecosystem.

2. Clarify that collaborative development of open-source AI components is exempt from AI Act requirements: To encourage open-source development, the Act should clarify that contributors to public repositories are not subject to the same regulatory requirements as commercial entities.

3. Support the AI Office’s coordination with the open-source ecosystem: The Act should encourage inclusive governance and collaboration between the AI Office and open-source developers to foster transparency and knowledge exchange.

4. Ensure practical and effective R&D exception: Allow limited real-world testing in different conditions, combining aspects of the Council’s approach and the Parliament’s Article 2(5d), to facilitate research and development without compromising safety and accountability.

5. Set proportional requirements for “foundation models”: Differentiate between various uses and development modalities of foundation models, including open source approaches, to ensure fair treatment and promote competition.

Open-source AI development offers several advantages, including transparency, inclusivity, and modularity. It allows stakeholders to collaborate and build on each other’s work, leading to more robust and diverse AI models. For instance, the EleutherAI community has become a leading open-source ML lab, releasing pre-trained models and code libraries that have enabled foundational research and reduced the barriers to developing large AI models.

Similarly, the BigScience project, which brought together over 1200 multidisciplinary researchers, highlights the importance of facilitating direct access to AI components across institutions and disciplines.

Such open collaborations have democratised access to large AI models, enabling researchers to fine-tune and adapt them to various languages and specific tasks—ultimately contributing to a more diverse and representative AI landscape.

Open research and development also promote transparency and accountability in AI systems. For example, LAION – a non-profit research organisation – released openCLIP models, which have been instrumental in identifying and addressing biases in AI applications. Open access to training data and model components has enabled researchers and the public to scrutinise the inner workings of AI systems and challenge misleading or erroneous claims.

The AI Act’s success depends on striking a balance between regulation and support for the open AI ecosystem. While openness and transparency are essential, regulation must also mitigate risks, ensure standards, and establish clear liability for AI systems’ potential harms.

As the EU sets the stage for regulating AI, embracing open source and open science will be critical to ensure that AI technology benefits all citizens.

By implementing the recommendations provided by organisations representing stakeholders in the open AI ecosystem, the AI Act can foster an environment of collaboration, transparency, and innovation, making Europe a leader in the responsible development and deployment of AI technologies.

(Photo by Nick Page on Unsplash)

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The act aims to regulate AI based on its potential to cause harm and follows a risk-based approach, prohibiting applications that pose an unacceptable risk while imposing strict regulations for high-risk use cases.

The timing of AI regulation has been a subject of debate, but Dragoș Tudorache, one of the European Parliament’s co-rapporteurs on the AI Act, emphasised that it is the right time to regulate AI due to its profound impact.

Dr Ventsislav Ivanov, AI Expert and Lecturer at Oxford Business College, said: “Regulating artificial intelligence is one of the most important political challenges of our time, and the EU should be congratulated for attempting to tame the risks associated with technologies that are already revolutionising our daily lives.

“As the chaos and controversy accompanying this vote show, this will be not an easy feat. Taking on the global tech companies and other interested parties will be akin to Hercules battling the seven-headed hydra.”

The adoption of the AI Act faced uncertainty as a political deal crumbled, leading to amendments from various political groups.

One of the main points of contention was the use of Remote Biometric Identification, with liberal and progressive lawmakers seeking to ban its real-time use except for ex-post investigations of serious crimes. The centre-right European People’s Party attempted to introduce exceptions for exceptional circumstances like terrorist attacks or missing persons, but their efforts were unsuccessful.

A tiered approach for AI models will be introduced with the act, including stricter regulations for foundation models and generative AI.

The European Parliament intends to introduce mandatory labelling for AI-generated content and mandate the disclosure of training data covered by copyright. This move comes as generative AI, exemplified by ChatGPT, gained widespread attention—prompting the European Commission to launch outreach initiatives to foster international alignment on AI rules.

MEPs made several significant changes to the AI Act, including expanding the list of prohibited practices to include subliminal techniques, biometric categorisation, predictive policing, internet-scraped facial recognition databases, and emotion recognition software.

An extra layer was introduced for high-risk AI applications and extended the list of high-risk areas and use cases in law enforcement, migration control, and recommender systems of prominent social media platforms.

Robin Röhm, CEO of Apheris, commented: “The passing of the plenary vote on the EU’s AI Act marks a significant milestone in AI regulation, but raises more questions than it answers. It will make it more difficult for start-ups to compete and means that investors are less likely to deploy capital into companies operating in the EU.

“It is critical that we allow for capital to flow to businesses, given the cost of building AI technology, but the risk-based approach to regulation proposed by the EU is likely to lead to a lot of extra burden for the European ecosystem and will make investing less attractive.”

With the European Parliament’s adoption of its position on the AI Act, interinstitutional negotiations will commence with the EU Council of Ministers and the European Commission. The negotiations – known as trilogues – will address key points of contention such as high-risk categories, fundamental rights, and foundation models.

Spain, which assumes the rotating presidency of the Council in July, has made finalising the AI law its top digital priority. The aim is to reach a deal by November, with multiple trilogues planned as a backup.

The negotiations are expected to intensify in the coming months as the EU seeks to establish comprehensive regulations for AI, balancing innovation and governance while ensuring the protection of fundamental rights.

“The key to good regulation is ensuring that safety concerns are addressed while not stifling innovation. It remains to be seen whether the EU can achieve this,” concludes Röhm.

(Image Credit: European Union 2023 / Mathieu Cugnot)

Similar: UK will host global AI summit to address potential risks

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This marks a major step in the development of AI regulation in Europe, as these are the first-ever rules for AI. The rules aim to ensure that AI systems are safe, transparent, traceable, and non-discriminatory.

After the vote, co-rapporteur Brando Benifei (S&D, Italy) said:

“We are on the verge of putting in place landmark legislation that must resist the challenge of time. It is crucial to build citizens’ trust in the development of AI, to set the European way for dealing with the extraordinary changes that are already happening, as well as to steer the political debate on AI at the global level.

We are confident our text balances the protection of fundamental rights with the need to provide legal certainty to businesses and stimulate innovation in Europe.”

Co-rapporteur Dragos Tudorache (Renew, Romania) added:

“Given the profound transformative impact AI will have on our societies and economies, the AI Act is very likely the most important piece of legislation in this mandate. It’s the first piece of legislation of this kind worldwide, which means that the EU can lead the way in making AI human-centric, trustworthy, and safe.

We have worked to support AI innovation in Europe and to give start-ups, SMEs and industry space to grow and innovate while protecting fundamental rights, strengthening democratic oversight, and ensuring a mature system of AI governance and enforcement.”

The rules are based on a risk-based approach and they establish obligations for providers and users depending on the level of risk that the AI system can generate. AI systems with an unacceptable level of risk to people’s safety would be strictly prohibited, including systems that deploy subliminal or purposefully manipulative techniques, exploit people’s vulnerabilities, or are used for social scoring.

MEPs also substantially amended the list of prohibited AI practices to include bans on intrusive and discriminatory uses of AI systems, such as real-time remote biometric identification systems in publicly accessible spaces, post-remote biometric identification systems (except for law enforcement purposes), biometric categorisation systems using sensitive characteristics, predictive policing systems, emotion recognition systems in law enforcement, border management, workplace, and educational institutions, and indiscriminate scraping of biometric data from social media or CCTV footage to create facial recognition databases.

MEPs also expanded the classification of high-risk areas to include harm to people’s health, safety, fundamental rights, or the environment. They also added AI systems that influence voters in political campaigns and recommender systems used by social media platforms to the high-risk list.

To boost AI innovation, MEPs added exemptions to these rules for research activities and AI components provided under open-source licenses. The new law also promotes regulatory sandboxes – or controlled environments established by public authorities – to test AI before its deployment.

MEPs want to boost citizens’ right to file complaints about AI systems and receive explanations of decisions based on high-risk AI systems that significantly impact their rights. MEPs also reformed the role of the EU AI Office, which would be tasked with monitoring how the AI rulebook is implemented.

Tim Wright, Tech and AI Regulatory Partner at London-based law firm Fladgate, commented:

“US-based AI developers will likely steal a march on their European competitors given the news that the EU parliamentary committees have green-lit its groundbreaking AI Act, where AI systems will need to be categorised according to their potential for harm from the outset. 

The US tech approach is typically to experiment first and, once market and product fit is established, to retrofit to other markets and their regulatory framework. This approach fosters innovation whereas EU-based AI developers will need to take note of the new rules and develop systems and processes which may take the edge off their ability to innovate.

The UK is adopting a similar approach to the US, although the proximity of the EU market means that UK-based developers are more likely to fall into step with the EU ruleset from the outset. However, the potential to experiment in a safe space – a regulatory sandbox – may prove very attractive.”

Before negotiations with the Council on the final form of the law can begin, this draft negotiating mandate needs to be endorsed by the whole Parliament, with the vote expected during the 12-15 June session.

(Photo by Denis Sebastian Tamas on Unsplash)

Related: UK details ‘pro-innovation’ approach to AI regulation

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This is about to change. 

As the EU finalizes its AI Act and generative AI continues to rapidly evolve, we will see the artificial intelligence regulatory landscape shift from general, suggested frameworks to more permanent laws. 

The EU AI Act has spurred significant conversations among business leaders: How can we prepare for stricter AI regulations? Should I proactively design AI that meets this criterion? How soon will it be before similar regulation is passed in the US?

Continue reading to better understand what AI regulation may look like for companies in the near future.  

How the EU AI Act will impact your business 

Like the EU’s General Data Protection Regulation (GDPR) released in 2018, the EU AI Act is expected to become a global standard for AI regulation. Parliament is scheduled to vote on the draft by the end of March 2023, and if this timeline is met, the final AI Act could be adopted by the end of the year. 

It’s highly predicted that the effects of the AI Act will be felt beyond the EU’s borders (read: Brussels effect), albeit it being European regulation. Organizations operating on an international scale will be required to directly conform to the legislation. Meanwhile, US and other independently-led companies will quickly realize that it’s in their best interest to comply with this regulation.

We’re beginning to see this already with other similar legislation like Canada’s Artificial Intelligence & Data Act proposal and New York City’s automated employment regulation. 

AI system risk categories

Under the AI Act, organizations’ AI systems will be classified into three risk categories, each with their own set of guidelines and consequences. 

• Unacceptable risk. AI systems that meet this level will be banned. This includes manipulative systems that cause harm, real-time biometric identification systems used in public spaces for law enforcement, and all forms of social scoring. 
• High risk. These AI systems include tools like job applicant scanning models and will be subject to specific legal requirements. 
• Limited and minimal risk. This category encompasses many of the AI applications businesses use today, including chatbots and AI-powered inventory management tools, and will largely be left unregulated. Customer-facing limited-risk applications, however, will require disclosure that AI is being used. 

What will AI regulation look like? 

Because the AI Act is still under draft, and its global effects are to be determined, we can’t say with certainty what regulation will look like for organizations. However, we do know that it will vary based on industry, the type of model you’re designing, and the risk category in which it falls. 

Regulation will likely include scrutiny with a third party, where your model is stress tested against the population you’re attempting to serve. These tests will evaluate questions including ‘Is the model performing within acceptable margins of error?’ and ‘Are you disclosing the nature and use of your model? ‘

For organizations with high-risk AI systems, the AI Act has already outlined several requirements: 

• Implementation of a risk-management system. 
• Data governance and management. 
• Technical documentation.
• Record keeping and logging. 
• Transparency and provision of information to users.
• Human oversight. 
• Accuracy, robustness, and cybersecurity.
• Conformity assessment. 
• Registration with the EU-member-state government.
• Post-market monitoring system. 

We can also expect regular reliability testing for models (similar to e-checks for cars) to become a more widespread service in the AI industry. 

How to prepare for AI regulations 

Many AI leaders have already been prioritizing trust and risk mitigation when designing and developing ML models. The sooner you accept AI regulation as our new reality, the more successful you will be in the future. 

Here are just a few steps organizations can take to prepare for stricter AI regulation: 

• Research and educate your teams on the types of regulation that will exist, and how it impacts your company today and in the future.  
• Audit your existing and planned models. Which risk category do they align with and which associated regulations will impact you most?
• Develop and adopt a framework for designing responsible AI solutions.
• Think through your AI risk mitigation strategy. How does it apply to existing models and ones designed in the future? What unexpected actions should you account for?  
• Establish an AI governance and reporting strategy that ensures multiple checks before a model goes live. 

In light of the AI Act and inevitable future regulation, ethical and fair AI design is no longer a “nice to have”, but a “must have”. How can your organization prepare for success?

(Photo by ALEXANDRE LALLEMAND on Unsplash)

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“The AI Act will define how the world regulates AI and we need to get it right, for developers and the open-source community,” said Dohmke.

Dohmke was born and grew up in Germany but now lives in the US. As such, he is all too aware of the widespread belief that the EU cannot lead when it comes to tech innovation.

“As a European, I love seeing how open-source AI innovations are beginning to break the narrative that only the US and China can lead on tech innovation.”

“I’ll be honest, as a European living in the United States, this is a pervasive – and often true – narrative. But this can change. And it’s already beginning to, thanks to open-source developers.”

AI will revolutionise just about every aspect of our lives. Regulation is vital to minimise the risks associated with AI while allowing the benefits to flourish.

“Together, OSS (Open Source Software) developers will use AI to help make our lives better. I have no doubt that OSS developers will help build AI innovations that empower those with disabilities, help us solve climate change, and save lives.”

A risk of overregulation is that it drives innovation elsewhere. Startups are more likely to establish themselves in countries like the US and China where they’re likely not subject to as strict regulations. Europe will find itself falling behind and having less influence on the global stage when it comes to AI.

“The AI Act is so crucial. This policy could well set the precedent for how the world regulates AI. It is foundationally important. Important for European technological leadership, and the future of the European economy itself. The AI Act must be fair and balanced for the open-source community.

“Policymakers should help us get there. The AI Act can foster democratised innovation and solidify Europe’s leadership in open, values-based artificial intelligence. That is why I believe that open-source developers should be exempt from the AI Act.”

In expanding on his belief that open-source developers should be exempt, Dohmke explains that the compliance burden should fall on those shipping products.

“OSS developers are often volunteers. Many are working two jobs. They are scientists, doctors, academics, professors, and university students alike. They don’t usually stand to profit from their contributions—and they certainly don’t have big budgets and compliance departments!”

EU lawmakers are hoping to agree on draft AI rules next month with the aim of winning the acceptance of member states by the end of the year.

“Open-source is forming the foundation of AI innovation in Europe. The US and China don’t have to win it all. Let’s break that narrative apart!

“Let’s give the open-source community the daylight and the clarity to grow their ideas and build them for the rest of the world! And by doing so, let’s give Europe the chance to be a leader in this new age of AI.”

GitHub’s policy paper on the AI Act can be found here.

(Image Credit: Collision Conf under CC BY 2.0 license)

Relevant: US and EU agree to collaborate on improving lives with AI

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During a session at this year’s AI & Big Data Expo Europe, a panel of experts provided their views on what businesses need to consider before deploying artificial intelligence.

Here’s a list of the panel’s participants:

• Moderator: Frans van Bruggen, Policy Officer for AI and FinTech at De Nederlandsche Bank (DNB)
• Aoibhinn Reddington, Artificial Intelligence Consultant at Deloitte
• Sabiha Majumder, Model Validator – Innovation & Projects at ABN AMRO Bank N.V
• Laura De Boel, Partner at Wilson Sonsini Goodrich & Rosati

The first question called for thoughts about current and upcoming regulations that affect AI deployments. As a lawyer, De Boel kicked things off by giving her take.

De Boel highlights the EU’s upcoming AI Act which builds upon the foundations of similar legislation such as GDPR but extends it for artificial intelligence.

“I think that it makes sense that the EU wants to regulate AI, and I think it makes sense that they are focusing on the highest risk AI systems,” says De Boel. “I just have a few concerns.”

De Boel’s first concern is how complex it will be for lawyers like herself.

“The AI Act creates many different responsibilities for different players. You’ve got providers of AI systems, users of AI systems, importers of AI systems into the EU — they all have responsibilities, and lawyers will have to figure it out,” De Boel explains.

The second concern is how costly this will all be for businesses.

“A concern that I have is that all these responsibilities are going to be burdensome, a lot of red tape for companies. That’s going to be costly — costly for SMEs, and costly for startups.”

Similar concerns were raised about GDPR. Critics argue that overreaching regulation drives innovation, investment, and jobs out of the Eurozone and leaves countries like the USA and China to lead the way.

Peter Wright, Solicitor and MD of Digital Law UK, once told AI News about GDPR: “You’ve got your Silicon Valley startup that can access large amounts of money from investors, access specialist knowledge in the field, and will not be fighting with one arm tied behind its back like a competitor in Europe.”

The concerns raised by De Boel echo Wright and it’s true that it will have a greater impact on startups and smaller companies who already face an uphill battle against established industry titans.

De Boel’s final concern on the topic is about enforcement and how the AI Act goes even further than GDPR’s already strict penalties for breaches.

“The AI act really copies the enforcement of GDPR but sets even higher fines of 30 million euros or six percent of annual turnover. So it’s really high fines,” comments De Boel.

“And we see with GDPR that when you give these types of powers, it is used.”

Outside of Europe, different laws apply. In the US, rules such as those around biometric recognition can vary greatly from state-to-state. China, meanwhile, recently introduced a law that requires companies to give the option for consumers to opt-out from things like personalised advertising.

Keeping up with all the ever-changing laws around the world that may impact your AI deployments is going to be a difficult task, but a failure to do so could result in severe penalties.

The financial sector is already subject to very strict regulations and has used statistical models for decades for things such as lending. The industry is now increasingly using AI for decision-making, which brings with it both great benefits and substantial risks.

“The EU requires auditing of all high-risk AI systems in all sectors, but the problem with external auditing is there could be internal data, decisions, or confidential information which cannot be shared with an external party,” explains Majumder.

Majumder goes on to explain that it’s therefore important to have a second line of opinions -which is internal to the organisation – but they look at it from an independent perspective, from a risk management perspective.

“So there are three lines of defense: First, when developing the model. Second, we’re assessing independently through risk management. Third, the auditors as the regulators,” Majumder concludes.

Of course, when AI is always making the right decisions then everything is great. When it inevitably doesn’t, it can be seriously damaging.

The EU is keen on banning AI for “unacceptable” risk purposes that may damage the livelihoods, safety, and rights of people. Three other categories (high risk, limited risk, and minimal/no risk) will be permitted, with decreasing amounts of legal obligations as you go down the scale.

“We can all agree that transparency is really important, right? Because let me ask you a question: If you apply for some kind of service, and you get denied, what do you want to know? Why am I being denied the service?” says Reddington.

“If you’re denied service by an algorithm who cannot come up with a reason, what is your reaction?”

There’s a growing consensus that XAI (Explainable AI) should be used in decision-making so that reasons for the outcome can always be traced. However, Bruggen makes the point that transparency may not always be a good thing — you may not want to give a terrorist or someone accused of a financial crime the reason why they’ve been denied a loan, for example.

Reddington believes this is why humans should not be taken out of the loop. The industry is far from reaching that level of AI anyway, but even if/when available there are the ethical reasons we shouldn’t want to remove human input and oversight entirely.

However, AI can also increase fairness.

Mojumder gives the example from her field of expertise, finance, where historical data is often used for decisions such as credit. Over time, people’s situations change but they could be stuck with struggling to get credit based on historical data.

“Instead of using historical credit rating as input, we can use new kinds of data like mobile data, utility bills, or education, and AI has made it possible for us,” explains Mojumder.

Of course, using such a relatively small dataset then poses its own problems.

The panel offered some fascinating insights on ethics in AI and the current and future regulatory environment. As with the AI industry generally, it’s rapidly advancing and hard to keep up with but critical to do so.

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