Detecting Ethical and Societal Risks – A systematic approach for responsible AI

Date: Wednesday, August 26, 2020 | Time: 8 am PDT | 11 am EDT

Panelists

Data driven solutions and AI applications create enormous value. Yet, the pace of tech is accelerating, and the profits can be seductive and lead to unintended pitfalls. Discrimination, privacy intrusion, unethical nudging and social exclusion occur more frequently. These risks are difficult to predict using traditional compliance tools. An integrated perspective is needed - one that incorporates the legal, technical, and societal aspects of any tech solution. 

Until recently, regulation has been lagging behind technological advancements. Today, every organization using data-driven technologies and AI must start to consider the concepts of explainability, transparency and accountability. Developments in the policy and regulatory environment are also changing rapidly. The EU has recently published guidelines on Trustworthy AI, raising a number of issues where organizations will eventually have to comply, and it is better to be proactive and gain first-hand knowledge sooner rather than later.

Organizations need practical tools to detect, mitigate and govern how their use of data and AI is scaling in a broader context. If left unattended, societal and ethical risks from data driven technologies and AI can have unintended negative consequences on people and society. In addition, they can violate the reputation of your company.

AI Sustainability Center together with MetricStream has launched the first commercially available risk scanning self-assessment tool which makes it possible to scan AI and data driven applications for exposure to ethical and societal risks and potential vulnerabilities. The result is a unique risk profile, providing a “health check” which assesses both your organization’s risk level, as well as the risks for your specific AI solution.

For more insights, join this webinar where our experts will discuss:

  • The shift in regulatory focus of AI - risks by the US and EU governments
  • Examples of ethical and societal risks associated with data driven solutions and AI
  • Practical tools and methods for detecting and mitigating ethical and societal AI risks, including company cases

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