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Why AI regulation requires unified industry collaboration

Industry leaders argue that regulating ethical AI requires collaboration, stressing that not every aspect of AI should be subject to regulation.

Why AI regulation requires unified industry collaboration
[Source photo: Fast Company Middle East]

As society enters the digital era, often called the Fourth Industrial Revolution, focus must be directed toward regulatory frameworks and ethical considerations, particularly in artificial intelligence.

While AI opens doors to seemingly limitless possibilities, amidst all the hype, it is equally crucial for regulations to be in place and for decision-makers to actively incorporate ethical considerations into the realm of AI.

During the second edition of Fast Company Middle East’s World Changing Ideas Summit, the Impact Council, in collaboration with Boston Consulting Group, featured industry leaders who shared insights on achieving the intersection of artificial intelligence and ethics. The panel, “Reshaping the Narrative: The Interplay of Ethics and Responsible Innovation,” offered valuable perspectives.’


While there’s no definite way to predict the future of AI, addressing current concerns is essential to prevent any future derailment of this borderless technology.

Akram Awad, Partner and Global Lead for Smart Cities at BCG, says that a concern for him is how people underestimate AI’s disruptive nature, positively and negatively. “It will change the fundamentals of how we work and live and could take us to an existential risk if we don’t do it properly. We are creating something that will be at some point at par with how humans think and act and work, which should fundamentally change how we deal with it,” mentions Awad. 

Amith Rajan, Executive Vice President and Head of Wholesale Digital Banking and NeoVentures at Mashreq Bank, expresses concern about the potential risk of overregulation. As more individuals and nations eagerly embrace AI, discussions are underway on establishing frameworks for AI governance and ethics, prompting the need for regulation.

“The pendulum never stays at equilibrium. We might just end up killing a lot of the innovation on the back of that. We need to balance what should be regulated and left to develop,” says Rajan. 

Amin Al Zarooni, Chief Executive Officer of Bedu, points out that while technology is evolving rapidly, regulations for the technology are progressing at a slower pace, creating an imbalance between the two.

We need to consider questions like, where is the regulation coming from? What can I restrict? What can I allow for marketing and advertising with technology that can be super beneficial, but also think about the harm against humans?” shares Al Zarooni.

Tim Carmichael, Former Chief Data Officer of Chalhoub Group, provides a different perspective, emphasizing that ethics is not a singular viewpoint. Instead, it is intertwined with individuals’ values, shaped by their cultural backgrounds, interactions, influencers, and influence on others.

“Trying to find a one-size-fits-all approach to ethics on anything is difficult. Applying that to something poorly understood as artificial intelligence will be challenging.”


Despite the concerns, AI has significant business opportunities to coexist with humans, fostering company growth.

Rajan notes that the banking industry is already subject to substantial regulation. Consequently, the sector is exploring ways to enhance customer experience through the integration of AI.

“We have a lot of data sitting with us. A lot of what we’re doing today, whether it’s on the retail banking side or whether it’s on the corporate banking side, is focused on how we make the lives of our customers easier. AI gives us some good tools for that,” he adds.

Al Zarooni, on the other hand, emphasizes that the application of AI depends on specific use cases and investigates which types of AI applications are suitable for each industry.

Meanwhile, Awad highlights the productivity benefits associated with AI augmentation. He refers to a research paper published by BCG, Harvard, Stanford, MIT, and other prominent institutions, revealing that, for specific segments, productivity for identical tasks increased by up to 40%.

“This signifies the opportunity AI can bring to the table of doing things faster at a better quality.”

Carmichael agrees, stating, “It’s like taking off the handcuffs from people locked in the struggle of repeated repetitive tasks. If you do that, that liberates them to do the things that only humans can do.”


When talking about AI and ethics, a crucial element to keep in mind that continues to come up is the biases within algorithms and how they can be better identified to provide more fairness in the outcome.

Biases originate primarily from the data, whereas inherited biases result from historical human practices reflected in the data. Additionally, biases arise in the data sourcing process, encompassing choices regarding the diversity of gender, language, cultures, and more. Furthermore, biases can emerge in the interpretation of AI outcomes.

In the early stages of AI, the focus was on inputting a data set, training the system, and identifying issues, making the conversation about biases more straightforward. However, as AI has progressed, the discussion has become more complex.

Awad says that we first need to be conscious about it. Next, there needs to be a clear set of tools that test for biases and samples of use cases that get reviewed.

Rajan backs Awad’s statement, stating, “The biases sit within the data.” However, he also mentions that stripping those biases out of the data removes the essence of the data itself and only creates more biases.

Instead, he suggests applying policies on top of the data. “As policy guardrails come in, the quality of your data will improve because the quality of your outcome will improve.” 

Carmichael says a possible solution is using AI to improve the quality of data feeding the AI, as long as it is understood that the data will be flawed. “No matter how good the algorithm, if the data going in is poor, it will struggle to deliver the outcomes you want.”

Even with all the work being done in the present moment with AI, businesses still need to set a realistic timeline of when regulations will come into place. “There is a lot of trial and error. There is a lot of involvement from the public in continuous feedback so that we can eliminate bias or try to achieve as much as ethics in the development and process,” says Al Zarooni.

Awad holds hope and notes that AI brings a lot of promise to the table.

“AI gives us a huge opportunity to save our planet. As we march toward COP28, AI can give us a lot when it comes to measuring emissions, mitigating them, improving the efficiency and productivity of renewable energy, adapting and increasing our resilience to some of those changes.”

He emphasizes, “These areas demonstrate that by placing AI strategically, be it in addressing climate change or making a social impact, we genuinely have the opportunity to unlock its potential for the benefit of humanity.”

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