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AI should not be a black box

Spats at OpenAI highlight the need for companies to become more transparent
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{"text":[[{"start":null,"text":"

Sam Altman, chief executive of OpenAI. Researchers once released papers on their work, but the rush for market share has ended such disclosures
"}],[{"start":8.23,"text":"Proponents and detractors of AI tend to agree that the technology will change the world. "},{"start":13.159,"text":"The likes of OpenAI’s Sam Altman see a future where humanity will flourish; critics prophesy societal disruption and excessive corporate power. "},{"start":20.977,"text":"Which prediction comes true depends in part on foundations laid today. "},{"start":24.907,"text":"Yet the recent disputes at OpenAI — including the departure of its co-founder and chief scientist — suggest key AI players have become too opaque for society to set the right course. "}],[{"start":35.480000000000004,"text":"An index developed at Stanford University finds transparency at AI leaders Google, Amazon, Meta and OpenAI falls short of what is needed. "},{"start":43.709,"text":"Though AI emerged through collaboration by researchers and experts across platforms, the companies have clammed up since OpenAI’s ChatGPT ushered in a commercial AI boom. "},{"start":52.989000000000004,"text":"Given the potential dangers of AI, these companies need to revert to their more open past. "}],[{"start":58.86,"text":"Transparency in AI falls into two main areas: the inputs and the models. "},{"start":63.577,"text":"Large language models, the foundation for generative AI such as OpenAI’s ChatGPT or Google’s Gemini, are trained by trawling the internet to analyse and learn from “data sets” that range from Reddit forums to Picasso paintings. "},{"start":75.969,"text":"In AI’s early days, researchers often disclosed their training data in scientific journals, allowing others to diagnose flaws by weighing the quality of inputs. "}],[{"start":85.6,"text":"Today, key players tend to withhold the details of their data to protect against copyright infringement suits and eke out a competitive advantage. "},{"start":93.217,"text":"This makes it difficult to assess the veracity of responses generated by AI. "},{"start":97.83399999999999,"text":"It also leaves writers, actors and other creatives without insight into whether their privacy or intellectual property has been knowingly violated. "}],[{"start":105.6,"text":"The models themselves lack transparency too. "},{"start":108.62899999999999,"text":"How a model interprets its inputs and generates language depends upon its design. "},{"start":113.184,"text":"AI firms tend to see the architecture of their model as their “secret sauce”: the ingenuity of OpenAI’s GPT-4 or Meta’s Llama pivots on the quality of its computation. "},{"start":122.439,"text":"AI researchers once released papers on their designs, but the rush for market share has ended such disclosures. "},{"start":128.469,"text":"Yet without the understanding of how a model functions, it is difficult to rate an AI’s outputs, limits and biases. "}],[{"start":135.22,"text":"All this opacity