Enterprises Must Establish Algorithmic Governance in Advance of Regulatory Mandates

As with other fields, technological developments go blazing ahead in advance of the regulators’ ability to define it.

As this vibrant AI landscape evolves, the spotlight inevitably falls on the indispensable role of algorithmic governance. This paramount concept underscores the pivotal participation of both public and private stakeholders. Companies contribute to the larger discourse surrounding algorithmic ethics by openly communicating and sharing their governance frameworks.

"The key to ensuring the responsible application of AI technology is algorithmic governance," writes Mark Esposito and Terence Tse of Hult Business School, Aurélie Jean and Guillaume Sibout of In Silico Veritas.

This article comprehensively delves into algorithmic governance's crucial role in rapidly advancing AI technologies and the need for proactive measures by enterprises. The authors stress the significance of algorithmic governance in ensuring responsible and ethical applications of AI technology, especially in light of the European Parliament's groundbreaking legal framework for overseeing AI systems based on their potential risk levels to citizens' fundamental rights.

Here are some takeaways:

• Crucial Role of Algorithmic Governance. The article underscores the paramount importance of algorithmic governance in overseeing AI technologies. It highlights how this multidimensional framework goes beyond ethical principles, acting as a comprehensive and systematic set of measures to ensure responsible AI development and deployment.
• Continuous Risk Assessment and Ethical Oversight. Successful algorithmic governance involves continual risk assessment, drafting of ethical principles, establishment of ethics committees, and employing explainability calculations to maintain transparency and ethical equilibrium in algorithmic decision-making.
• Proactive Organizational Integration. Enterprises are encouraged to identify precise business proactively needs suitable for algorithmic technology. Collaborating between technical and business teams and establishing, validating, and integrating governance frameworks within organizational operations is crucial.

Dr Mark Esposito is a Professor of Business & Economics at Hult International Business School, where he directs the Futures Impact Lab.

Aurélie Jean is a computational scientist, entrepreneur and author. She is now running two companies, including a deeptech AI startup in early detection of breast cancer.

Terence Tse is a Professor of Finance at Hult International Business School. He is also a co-founder and Executive Director of Nexus FrontierTech.

Guillaume Sibout is a Specialist in Digital Humanities. He has held various communication and marketing management positions in the finance sector.

You can read the full article for free on our website.