Future Dreaming 2024 | Artificial intelligence in career guidance "How is AI being used in career guidance?, What should we be careful of?"

Editor's Notes

1. Impressions on guidance: General statements are approximately tailored to the context and have reasonable caveats, including recommendations to reach out to people Words convey some empathy but not sensitive to the direct feedback (e.g. keeps producing fairly large itemised lists) Not actually delivering guidance, more of a single response to a single question with suggested actions for the user No asking questions to gather more context, no breaking up the conversation into smaller units, no trust building/contracting, no probing for underlying issues (e.g. why are feeling under pressure) etc. In practice, treating guidance questions more like advice. If more proactive as a user, can get some more value out of it It may be possible to fine-tune models to act more like an empathetic conversation, e.g. with InstructGPT and successors, but this is not available off the shelf, and if we want to RLHF it wouldn’t be a quick process either Impressions on advice: Doesn’t ask for context – without context it is hard to offer good advice. The generic statements are fine, and perhaps sharing those is fine, but it should say that a good answer requires context and ask if user willing to answer questions. No challenge, probing, testing – but perhaps this is okay (as in accept this by design) If ask for specific opportunities, it is likely to either refuse to answer (fine) or hallucinate details Acknowledges it’s an AI language model On the face of it, the simpler question turns out to be strangely harder for the LLM, perhaps because generic answers are less appropriate in this case. You would need the LLM plugged into local LMI and trained to probe for context in these kinds of contexts.
2. People have been working on chatbot type models since the early years of computers, such as MIT's ELIZA in 1966 - a chatbot with scripts designed to imitate a therapist or psychologist. In the last few years, there has been an explosion of capability. OpenAi's first GPT model, GPT1 came out in 2016, but the impressive results really began in 2020 with GPT-3, which had 175 billion parameters. GPT-3 is basically a very good next word predictor. And if you think about it, to reliably predict the next word and then the next and the next, you need to encode certain reasoning and world modelling abilities to do it better. This is what we see with the LLMs - to various levels of ability - albeit with plenty of mistakes, given that it isn't actually grounded in the world at this stage and doesn't have a way of checking its reasoning separately from its corpus of text. GPT-3 sucked up about 500 billion tokens, approximately equivalent to words, mostly from online material. You then provide it with a prompt, which might be a few words or whole pages, and it then continues the text with what seems plausible given the vast corpus it has been trained. This isn't really a chatbot. If you show it an example conversation, it will continue the conversation, but keep producing text for both sides until told to stop. The usefulness of the result depends heavily on both the fine-tuning of the model and the quality of the prompt written immediately prior to the next word prediction, giving rise to the first of many grandiose careers predictions from the technology: that a new job called prompt engineer would seen be a major employer. At the end of Nov 2022, the world of LLMs changed. The same core model in GPT-3 was wrapped up with various behind-the-scenes fine-tuning and prompting to create something that worked intuitively as a fully natural language chatbot, rather than needing the user to provide the necessary prompts and illustrative examples to elicit the desired response: ChatGPT. The success of this, reaching 1 million users within 5 days of launch, sent the tech world into meltdown, with Microsoft, Facebook, Google, and later X/Twitter launching their own branded versions (Microsoft’s Bing is based on OpenAI).