Conference programme

A dynamic session which will enable delegates to select from a menu of hot topics mainly relating to artificial intelligence (AI) from the perspective of the intellectual property, communication, technology, art, media and space sectors, and to participate in roundtable discussions.

Topical AI-related issues will be selected to stimulate a lively debate. Moderators on each table will introduce the table topic and the participants do the rest.

This session will delve into the creative industries that rely on the exploitation of the economic right of copyright, including, music, film art and design. It will look at the challenges creators are facing with the increasing use of artificial intelligence (AI), legal actions by guilds and associations, and the relevance to the recent actors’ strike. The panel of experts will also discuss the issues around the use of copyright protected works in datasets training AI and will examine fair or (un)fair use in respect of potential copyright infringement.

With the recent advance of generative artificial intelligence (AI), an increasing number of service providers, platforms and apps rely on AI as part of their working processes. However, just like humans, AI systems tend to be or become “biased”. This bias affects the media industry on many levels: entertainment media giants such as Netflix use AI systems to enhance their efficiency but are now also experiencing the negative side-effects of AI bias. The power of media as the “Fourth Estate” is well-known, and this session, just a few days after the US presidential election, will examine how AI bias may affect election outcomes and the risks that AI bias may pose in the news media. The panel will, in addition, examine what tech companies can do (and indeed do) to prevent and control bias when designing AI systems. Finally, the legal risks concerning AI bias specific to these industry practices will also be assessed, in light of the new AI legislation.

Power, cooling and connectivity requirements for AI result in significant bottlenecks emphasised by scarcity of microprocessors. The outcome is a new playing field for information and communication technology (ICT) infrastructure.

With skyrocketing power and water consumption, current AI-powered data centres are putting huge pressure on grids and on civil infrastructure, with a direct impact on the way AI data centres are built. Resulting operating costs become deterrents for many players.

In this initial phase, small data centres have been favoured (from 1MWh to 4MWh). However, plans shared by Big Tech forecast gigawatt hour (GWh) or more data centres to be operated soon. This exponential growth in terms of capacity requirements results from computer power hungry large language model (LLM) training and fine tuning, but also from inference workloads, each category requesting different needs in terms of connectivity, latency and more generally service-level agreements (SLAs).

Impact on the value chain will be significant. All players will have to revisit their business model, in a race for capacity and efficiency, with a growing number of partnership pre-empting access to resources.