Opinions expressed by Digital Journal contributors are their own.
As the global AI race heats up, AI regulation is the hot topic for discussion, and industry experts are now looking at opportunities for collaboration between academia and industry to harness the opportunities.
At the fascinating inaugural TEDAI event in Vienna recently, a thought-provoking talk on ‘Europe’s next steps in AI innovation’ took place in which experts spoke in relation to the EU AI Act, which was the first attempt at regulating Artificial Intelligence in the world. Its aim is to shape Europe’s digital future by positioning it as the global leader in ethical and human-centric AI while simultaneously attempting to ensure its competitiveness.
Despite the Act’s attempts to mitigate the potential risks involved in AI, some are sceptical that the Act will stimulate innovation, arguing the Act fails to provide legal certainty to AI developers. Concerns also arise from regulation’s supposedly limited ability to assess all risks posed by AI, considering generative AI (such as ChatGPT, Llama, and Gemini) can be moulded for an infinite range of purposes, meaning any attempt at regulation could quickly become outdated.
At TEDAI, experts acknowledged some of the concerns about the limitations of the Act but pointed to how academia could help to address them.
Speaking at the three-day event, Sepp Hochreiter, one of the world’s leading computer scientists and the head of Linz Institute of Technology AI Lab, argued that there needs to be greater collaboration between academia and industries in the AI space.
Hochreiter pointed out that we can already see a close relationship between AI and Industry in Switzerland and Amsterdam through new AI institutes in universities. Companies such as Google and Nvidia have R&D facilities in Switzerland and collaborate with universities on AI projects by funding research initiatives, particularly at ETH Zurich.
Therefore, by collating the greatest minds on AI and its regulation, we can reasonably expect a deeper understanding of how the industry can work alongside regulators and within the EU AI Act. Through collaboration between academics and AI like we witness in Switzerland we can address concerns of innovation voiced by regulation sceptics and foster competition.
The collaborative opportunities are considerable. Knowledge Transfer Partnerships (KTPs) between university departments and AI developers are already helping to solve industry challenges. The UK has made KTPs a central theme for AI development as part of its 2021 National AI Strategy. The University of Surrey has a KTP with Yeltech to develop an AI-enabled predictive maintenance platform which provides asset managers with advanced information and allows them to predict when asset failures occur.
However, simply encouraging collaboration is insufficient to address those more sceptical of regulation. Ramin Hasani, Liquid Neural Networks co-inventor and Liquid AI CEO, expanded on Hochreiter’s notion by advocating for trust between the work of academics and industry professionals.
Trust enables collaboration to flourish, allowing a wide range of ideas and suggestions to be taken seriously. Academia could also be a testing ground for new technologies related to AI, thus driving and accelerating innovation. A close relationship helps facilitate the sharing of knowledge and ideas which inevitably leads to new methodologies and innovation by promoting an open dialogue across disciplines.
Cyber expert and entrepreneur, Rotem Farkash, who was also in attendance at the event, supported the idea of enhancing trust and collaboration between academics and the AI industry. He said: “The discussion around regulation is important for an industry that has considerable growth potential, but trust and collaboration between academics and the industry are a necessity to prevent regulation from stymying innovation at such a critical point in AI development.”
While the concerns of regulation sceptics should not be ignored, valuable suggestions from industry experts on the collaboration between academia and the AI industry is vital to maintaining innovation in the wake of groundbreaking regulation.
