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Although humans andartificial intelligence(AI ) systems"think " very other than , raw inquiry has revealed that three-toed sloth sometimes make decisions as irrationally as we do .
In almost half of the scenarios test in a new bailiwick , ChatGPT demonstrate many of the most coarse human decision - making biases . print April 8 . in the journalManufacturing & Service Operations Management , the findings are the first to evaluate ChatGPT ’s behavior across 18 well - known cognitive biases found in human psychology .
The paper ’s authors , from five academic initiation across Canada and Australia , tested OpenAI ’s GPT-3.5 and GPT-4 — the two big language manakin ( LLMs ) powering ChatGPT — and discovered that despite being " imposingly consistent " in their logical thinking , they ’re far from immune to human - like flaws .
What ’s more , such consistency itself has both cocksure and negative effects , the authors say .
" Managers will benefit most by using these pecker for problems that have a vindicated , formulaic solution , " subject lead - authorYang Chen , assistant professor of operation management at the Ivey Business School , said in astatement . " But if you ’re using them for subjective or preference - driven decision , trample cautiously . "
The cogitation aim commonly known human biases , including risk aversion , overconfidence and the endowment effect ( where we assign more economic value to things we own ) and use them to prompt given to ChatGPT to see if it would fall into the same traps as humans .
Rational decisions — sometimes
The scientists involve the LLMs hypothetic interrogative taken from traditional psychological science , and in the context of real - world commercial pertinence , in areas like inventory management or supplier negotiations . The aim was to see not just whether AI would mimic human diagonal but whether it would still do so when ask questions from unlike business organization domains .
GPT-4 outdo GPT-3.5 when answering trouble with clear mathematical solution , showing fewer error in probability and logic - found scenarios . But in subjective simulation , such as whether to choose a risky alternative to realize a gain , the chatbot often mirrored the irrational preferences human being run to show .
" GPT-4 shows a stronger penchant for sure thing than even humans do , " the researchers wrote in the paper , referring to the inclination for AI to tend towards safer and more predictable outcomes when given ambiguous task .
More significantly , the chatbots ' behaviors remained mostly stable whether the head were framed as abstract psychological problem or operational business summons . The study concluded that the bias shown were n’t just a product of memorized examples — but part of how AI reasons .
One of the surprising outcomes of the study was the elbow room GPT-4 sometimes inflate human - corresponding errors . " In the verification bias task , GPT-4 always gave biased reception , " the source compose in the study . It also showed a more marked leaning for the live - hand fallacy ( the bias to wait patterns in randomness ) than GPT 3.5 .
Conversely , ChatGPT did manage to avoid some unwashed human bias , let in al-Qaeda - rate neglect ( where we ignore statistical facts in favour of anecdotal or case - specific information ) and the sunk - cost fallacy ( where decision qualification is influenced by a cost that has already been get , allowing irrelevant info to swarm judicial decision ) .
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agree to the authors , ChatGPT ’s man - like biases make out from grooming data point that comprise the cognitive bias and heuristics humans march . Those trend are reinforced during fine - tuning , especially when human feedback further favour plausible response over intellectual ones . When they come up against more ambiguous tasks , AI skews towards human abstract thought patterns more so than direct logic .
" If you need exact , unbiassed conclusion support , use GPT in areas where you ’d already trust a reckoner , " Chen said . When the issue depends more on subjective or strategical inputs , however , human supervision is more significant , even if it ’s adjusting the substance abuser prompts to redress known diagonal .
" AI should be treated like an employee who makes important decision — it needs oversight and honorable guidelines , " co - authorMeena Andiappan , an associate professor of human resource and management at McMaster University , Canada , said in the financial statement . " Otherwise , we risk automatise flawed mentation instead of meliorate it . "
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