Privacy Breaches, Ethical Quandaries and Bias Challenges Loom Large in the AI Era

Graeme Grovum, Head of Legal Technology and Client Services at Allens, highlighted several ethical quandaries related to artificial intelligence (AI) in a recent interview with the Docket. 

More specifically, he raised concerns about the misuse of personal data, citing examples like the Cambridge Analytica scandal and the challenges posed by persuasive AI in manipulating public opinion through social media. He also discussed the blurring lines between generative AI (GenAI) and other advanced technologies. 

The accuracy of algorithms, the mosaic theory, and the erosion of personal privacy are key ethical issues. Grovum highlights the growing impact of generative AI, suggesting that 2022 might be remembered as the last year when content could reliably be assumed to be human generated. The rise of AI-generated content, including disinformation, poses challenges for discerning truth and authenticity.

“It might be cold comfort, in a world already plagued by disinformation campaigns, to ‘appreciate’ the fact that disinformation was at least created by human(s) until 2023,” he said.

Grovum also addressed the environmental impact of AI, with a focus on the computational resources required for generative AI. He discussed the energy-intensive nature of AI tasks, drawing attention to the carbon footprint associated with training complex models and presenting a comparison of energy consumption among different types of generative AI that show generative tasks and image-related AI activities are more resource-intensive. 

The interview pinpointed bias in AI as another ethical issue. Grovum emphasized the contextual aspects of bias and the challenge of managing public consciousness when constructing datasets. 

Grovum called for a comprehensive understanding of the ethical implications of AI, from environmental concerns to issues of privacy and bias. He cited the need for proactive discussions, forums, and the inclusion of ethical considerations in AI governance policies to guide organizations in navigating these challenges.