Introduction Artificial Intelligence (AI) systems have come a long way since 2016, when Microsoft released Tay, an AI chatbot which had to be shut down within a day after spewing racist and anti-Semitic tweets. [1] In 2022, OpenAI introduced ChatGPT, beginning a new era for generative AI where algorithms could churn out diverse content at scale; its champions say it could contribute trillions of dollars to the world economy. [2] The latest version of ChatGPT, at the time of writing, can process and produce information across different modalities like text, image, and video. [3] If the Tay experience taught the world anything, however, it is that there is a need for guardrails for AI algorithms that learn dynamically and interactively from harmful user behaviour or that draw patterns and inferences from widely prevalent human conduct with negative social, economic and political consequences. While AI’s potential for generating explicitly harmful outputs may have reduced since Tay, its effects have become less apparent as a result of the widespread use and re-use of common datasets with inherent biases across different algorithms and models. [4] Such consequential but less visible harms have come to be entrenched and pervasive as companies continue to develop and embed AI capabilities in their products, services, processes, and decision-making. [5]
Authors
- Attribution
- Samir Saran, Anulekha Nandi, and Sameer Patil, “‘Moving Horizons’: A Responsive and Risk-Based Regulatory Framework for A.I.,” ORF Special Report No. 229 , June 2024, Observer Research Foundation.
- Published in
- India