{"id":28842,"date":"2023-08-01T10:31:53","date_gmt":"2023-08-01T16:31:53","guid":{"rendered":"https:\/\/otech.uaeh.edu.mx\/noti\/?p=28842"},"modified":"2023-08-01T15:52:31","modified_gmt":"2023-08-01T21:52:31","slug":"chatgpt-is-replacing-humans-in-studies-on-human-behavior-and-it-works-surprisingly-well","status":"publish","type":"post","link":"https:\/\/otech.uaeh.edu.mx\/noti\/ia\/chatgpt-is-replacing-humans-in-studies-on-human-behavior-and-it-works-surprisingly-well\/","title":{"rendered":"ChatGPT Is Replacing Humans in Studies on Human Behavior\u2014and It Works Surprisingly Well"},"content":{"rendered":"

Parts Unknown<\/a>\u00a0de Anthony Bourdain .\u00a0<\/em>En cada episodio, el chef visita aldeas remotas en todo el mundo, documentando las vidas, comidas y culturas de las tribus regionales con un coraz\u00f3n y una mente abiertos.<\/span><\/p>\n

The show provides a glimpse into humanity\u2019s astonishing diversity. Social scientists have a similar goal\u2014understanding the behavior of different people, groups, and cultures\u2014but use a variety of methods in controlled situations. For both, the stars of these pursuits are the subjects: humans.<\/span><\/p>\n

But what if you replaced humans with AI chatbots?<\/span><\/p>\n

The idea sounds preposterous. Yet thanks to the advent of ChatGPT and other large language models (LLMs), social scientists are flirting with the idea of using these tools to rapidly construct diverse groups of \u201csimulated humans\u201d and run experiments to probe their behavior and values as a proxy to their biological counterparts.<\/span><\/p>\n

If you\u2019re imagining digitally recreated human minds, that\u2019s not it. The idea is to tap into ChatGPT\u2019s expertise at mimicking human responses. Because the models scrape enormous amounts of online data\u2014blogs, Youtube comments, fan fiction, books\u2014they readily capture relationships between words in multiple languages. These sophisticated algorithms can also decode nuanced aspects of language, such as irony, sarcasm, metaphors, and emotional tones, a critical aspect of human communication in every culture. These strengths set LLMs up to mimic multiple synthetic personalities with a wide range of beliefs.<\/span><\/p>\n

Another bonus? Compared to human participants, ChatGPT and other LLMs don\u2019t get tired, allowing scientists to collect data and test theories about human behavior with unprecedented speed.<\/span><\/p>\n

The idea, though controversial, already has support.\u00a0A recent article\u00a0<\/a>reviewing the nascent field found that in certain carefully-designed scenarios, ChatGPT\u2019s responses correlated with those of roughly 95 percent of human participants.<\/span><\/p>\n

AI \u201ccould change the game for social science research,\u201d\u00a0said<\/a>\u00a0Dr. Igor Grossman at the University of Waterloo, who with colleagues recently penned a look-ahead article in\u00a0Science<\/em>. The key for using\u00a0Homo silicus<\/em>\u00a0in research? Careful bias management and data fidelity, said the team.<\/span><\/p>\n

Probing the Human Societal Mind<\/span><\/h2>\n

What exactly is social science?<\/span><\/p>\n

Put simply, it\u2019s studying how humans\u2014either as individuals or as a group\u2014behave under different circumstances, how they interact with each other and develop as a culture. It\u2019s an umbrella of academic pursuit with multiple branches: economics, political science, anthropology, and psychology.<\/span><\/p>\n

The discipline tackles a wide range of topics prominent in the current zeitgeist. What\u2019s the impact of social media on mental health? What are current public attitudes towards climate change as severe weather episodes increase? How do different cultures value methods of communication\u2014and what triggers misunderstandings?<\/span><\/p>\n

A social science study starts with a question and a hypothesis. One of my favorites: do cultures tolerate body odor differently? (No kidding,\u00a0the topic<\/a>\u00a0has been studied<\/a>\u00a0quite a bit, and yes,\u00a0there is a difference<\/a>!)<\/span><\/p>\n

Scientists then use a variety of methods, like questionnaires, behavioral tests, observation, and modeling to test their ideas. Surveys are an especially popular tool, because the questions can be stringently designed and vetted and easily reach a wide range of people when distributed online. Scientists then analyze written responses and draw insights into human behavior. In other words, a participant\u2019s use of language is critical for these studies.<\/span><\/p>\n

So how does ChatGPT fit in?<\/span><\/p>\n

The \u2018Homo Silicus\u2019<\/span><\/h2>\n

To Grossman, the LLMs behind chatbots such as ChatGPT or Google\u2019s Bard represent an unprecedented opportunity to redesign social science experiments.<\/span><\/p>\n

Because they are trained on massive datasets, LLMs \u201ccan represent a vast array of human experiences and perspectives,\u201d said the authors. Because the models \u201croam\u201d freely without borders across the internet\u2014like people who often travel internationally\u2014they may adopt and display a wider range of responses compared to recruited human subjects.<\/span><\/p>\n

ChatGPT also doesn\u2019t get influenced by other members of a study or get tired, potentially allowing it to generate less biased responses. These traits may be especially useful in \u201chigh-risk projects\u201d\u2014for example, mimicking the responses of people living in countries at war or under difficult regimes through social media posts. In turn, the responses could inform real-world interventions.<\/span><\/p>\n

Similarly, LLMs trained on cultural hot topics such as gender identity or misinformation could reproduce different theoretical or ideological schools of thought to inform policies. Rather than painstakingly polling hundreds of thousands of human participants, the AI can rapidly generate responses based on online discourse.<\/span><\/p>\n

Potential real-life uses aside, LLMs can also act as digital subjects that interact with human participants in social science experiments, somewhat similar to nonplayer characters (NPC) in video games. For example, the LLM could adopt different \u201cpersonalities\u201d and interact with human volunteers across the globe online using text by asking them the same question. Because algorithms don\u2019t sleep, it could run 24\/7. The resulting data may then help scientists explore how diverse cultures evaluate similar information and how opinions\u2014and misinformation\u2014spread.<\/span><\/p>\n

Baby Steps<\/span><\/h2>\n

The idea of using chatbots in lieu of humans in studies isn\u2019t yet mainstream.<\/span><\/p>\n

But there\u2019s early proof that it could work. A\u00a0preprint study<\/a>\u00a0released this month from Georgia Tech, Microsoft Research, and Olin College found that an LLM replicated human responses in numerous classical psychology experiments, including the infamous\u00a0Milgram shock experiments<\/a>.<\/span><\/p>\n

Yet a critical question remains: how well can these models really capture a human\u2019s response?<\/span><\/p>\n

There are several stumbling blocks.<\/span><\/p>\n

First is the quality of the algorithm and the training data. Most online content is dominated by just a handful of languages. An LLM trained on these data could easily mimic the sentiment, perspective, or even moral judgment of people who use those languages\u2014in turn inheriting bias from the training data.<\/span><\/p>\n

\u201cEsta reproducci\u00f3n del sesgo es una gran preocupaci\u00f3n porque podr\u00eda amplificar las mismas disparidades que los cient\u00edficos sociales se esfuerzan por descubrir en su investigaci\u00f3n\u201d, dijo Grossman.<\/span><\/p>\n

A algunos cient\u00edficos tambi\u00e9n les preocupa que los LLM solo est\u00e9n\u00a0regurgitando<\/a>\u00a0lo que se les dice.\u00a0Es la ant\u00edtesis de un estudio de ciencias sociales, en el que el punto principal es capturar a la humanidad en toda su belleza diversa y compleja.\u00a0Por otro lado, se sabe que ChatGPT y modelos similares \u201c\u00a0alucinan<\/a>\u00a0\u201d, inventando informaci\u00f3n que suena plausible pero es falsa.<\/span><\/p>\n

Por ahora, \u201clos grandes modelos de lenguaje se basan en ‘sombras’ de experiencias humanas\u201d, dijo Grossman.\u00a0Debido a que estos sistemas de IA son en gran medida cajas negras, es dif\u00edcil entender c\u00f3mo o por qu\u00e9 generan ciertas respuestas, un poco preocupante cuando se usan como representantes humanos en experimentos de comportamiento.<\/span><\/p>\n

A pesar de las limitaciones, “los LLM permiten a los cient\u00edficos sociales romper con los m\u00e9todos de investigaci\u00f3n tradicionales y abordar su trabajo de manera innovadora”, dijeron los autores.\u00a0Como primer paso, Homo silicus podr\u00eda ayudar a intercambiar ideas y probar r\u00e1pidamente hip\u00f3tesis, y las prometedoras se validar\u00edan a\u00fan m\u00e1s en poblaciones humanas.<\/span><\/p>\n

Pero para que las ciencias sociales realmente den la bienvenida a la IA, deber\u00e1 haber transparencia, equidad e igualdad de acceso a estos poderosos sistemas.\u00a0Los LLM son dif\u00edciles y costosos de capacitar, y los modelos recientes se cierran cada vez m\u00e1s detr\u00e1s de fuertes muros de pago.<\/span><\/p>\n

\u201cDebemos asegurarnos de que los LLM de ciencias sociales, como todos los modelos cient\u00edficos, sean de c\u00f3digo abierto, lo que significa que sus algoritmos e, idealmente, los datos est\u00e9n disponibles para que todos puedan examinarlos, probarlos y modificarlos\u201d, dijo la autora del estudio, la Dra. Dawn Parker de la\u00a0Universidad<\/a>\u00a0de Waterloo.\u00a0\u201cSolo manteniendo la transparencia y la replicabilidad podemos asegurarnos de que la investigaci\u00f3n en ciencias sociales asistida por IA realmente contribuya a nuestra comprensi\u00f3n de la experiencia humana\u201d.<\/span><\/p>\n

Fuente:<\/p>\n

Fan, S. (2023, 25 julio). ChatGPT is replacing humans in studies on human behavior\u2014and it works surprisingly well<\/i>. Singularity Hub. https:\/\/singularityhub.com\/2023\/07\/25\/chatgpt-is-replacing-humans-in-studies-on-human-behavior-and-its-working-surprisingly-well\/<\/p>\n","protected":false},"excerpt":{"rendered":"

Parts Unknown\u00a0de Anthony Bourdain .\u00a0En cada episodio, el chef visita aldeas remotas en todo el mundo, documentando las vidas, comidas y culturas de las tribus regionales con un coraz\u00f3n y una mente abiertos.<\/p>\n","protected":false},"author":1,"featured_media":28843,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[361],"tags":[],"class_list":["post-28842","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ia"],"yoast_head":"\nChatGPT Is Replacing Humans in Studies on Human Behavior\u2014and It Works Surprisingly Well - Observatorio Tecnol\u00f3gico de Hidalgo<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/otech.uaeh.edu.mx\/noti\/ia\/chatgpt-is-replacing-humans-in-studies-on-human-behavior-and-it-works-surprisingly-well\/\" 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