Key idea: The main ethical challenges of AI fall into four broad categories: digital amplification, discrimination, security and control and inequality.
Original author and publication date: Open Access News – November 21, 2022
Futurizonte Editor’s Note: The list above makes clear that AI is a threat, regardless of how helpful and useful is for us.
From the article:
With greater scrutiny of tech practices and calls for transparency, businesses must manage the deployment of smart AI while ensuring privacy safeguards, preventing bias in algorithmic decision-making, and meeting guidelines in highly regulated industries. In this article, I look at five ways leaders can future-proof their businesses against these risks.
Staying ahead of regulatory changes
Regulating AI is a multifaceted and difficult challenge, and as a result, the regulatory landscape is a consistently evolving environment. However, the issue of unethical and biased AI is becoming critical as organizations are increasingly relying on algorithms to support their decisions – and we will undoubtedly see the ramp-up of regulatory scrutiny in the coming years as a result. To avoid the consequences of financial and reputational damage from unethical AI, organizations will need to get ahead of the curve.
This will mean developing a comprehensive AI risk framework to articulate and maintain ethical standards.
Unfortunately, at our current pace of innovation, many companies lack visibility into the risk of their own models and AI solutions, and not all algorithms require the same scrutiny.
When considering future regulatory changes, organizations should ensure they tailor their framework to their industry; for example, regulators are likely to exempt low-risk AI systems that pose no risks to human rights and safety, while financial and healthcare industries will require rigorous guardrails.