An Ethical AI Never Says "I" - Paola Writes
Large language models (LLMs) have sparked vast debate since OpenAI released ChatGPT to the public last November, whipping the Internet into a frenzy since the latest version based on GPT-4 became available to subscribers on March 14. Microsoft built an LLM from OpenAI into the new Bing chatbot it launched in February, causing a sensation as the first potential threat to Google’s dominance in search. ChatGPT’s statistical brute-force approach gained smarts and finesse from an infusion of symbolic AI through the Wolfram|Alpha plug-in announced on March 23. Every day brings a new, exciting possibility to do more things with LLMs.
The undeniable success of LLMs and the many practical uses being documented by the minute have overshadowed the long-standing discussion around what it means for an AI system to be reliable and ethical. [1] Even more puzzlingly, no one – to my knowledge – has yet proposed a simple safeguard that OpenAI, Microsoft, Alphabet, Meta and other platforms should adopt in order to mitigate some of the harms that can come to humans from the statistical wizardry of LLMs: configuring and training these models so that they do not answer in the first person.
A model taught, through reinforcement learning, that answers containing “I”, “me”, “my” are to be avoided as off limits would be much less likely to spew out meaningless utterances such as “I feel”, “I want”, “believe me”, “trust me”, “I love you”, “I hate you”, and much else that enterprising experimenters have coaxed out of ChatGPT and its peers. Feelings, desires, personality, and even sentience, so far the privilege of biological, living beings, have been mistakenly attributed to highly sophisticated algorithms, designed to run on silicon-based integrated circuits and arrange “tokens” consisting of words into plausible sequences. The wrongful personalization of the AI software has not only provoked experiments, debates and tweetstorms which are a massive waste of human time and computing power. As multitudes of fictitious “Is” have emerged from silicon, many of them have already turned malevolent. As Professor Joanna J. Bryson has pointed out, without moral agency, AI’s “ linguistic compatibility has become a security weakness, a cheap and easy way by which our society can be hacked and our emotions exploited.”
