{"id":1128306,"date":"2023-04-13T10:59:33","date_gmt":"2023-04-13T14:59:33","guid":{"rendered":"https:\/\/www.prime-wow.com\/?p=1128306"},"modified":"2023-04-13T10:59:33","modified_gmt":"2023-04-13T14:59:33","slug":"how-anthropomorphism-hinders-ai-education","status":"publish","type":"post","link":"https:\/\/www.prime-wow.com\/?p=1128306","title":{"rendered":"How anthropomorphism hinders AI education"},"content":{"rendered":"

In the 1950s, Alan Turing explored the central question of artificial intelligence (AI). He thought that the original question, \u201cCan machines think?\u201d, would not provide useful answers because the terms \u201cmachine\u201d and \u201cthink\u201d are hard to define. Instead, he proposed changing the question to something more provable: \u201cCan a computer imitate intelligent behaviour well enough to convince someone they are talking to a human?<\/a>\u201d This is commonly referred to as the Turing test.<\/p>\n

It\u2019s been hard to miss the newest generation of AI chatbots that companies have released over the last year. News articles and stories about them seem to be everywhere at the moment. So you may have heard of machine learning (ML) chatbots such as ChatGPT and LaMDA. These chatbots are advanced enough to have caused renewed discussions about the Turing Test and whether the chatbots are sentient<\/a>.<\/p>\n

Chatbots are not sentient<\/strong><\/h2>\n

Without any knowledge of how people create such chatbots, it\u2019s easy to imagine how someone might develop an incorrect mental model around these chatbots being living entities. With some awareness of Sci-Fi stories, you might even start to imagine what they could look like or associate a gender with them.<\/p>\n

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Image: Alan Warburton \/ \u00a9 BBC \/ Better Images of AI<\/a> \/ Quantified Human \/ CC BY 4.0<\/a><\/figcaption><\/figure>\n<\/div>\n

The reality is that these new chatbots are applications based on a large language model (LLM) \u2014 a type of machine learning model that has been trained with huge quantities of text, written by people and taken from places such as books and the internet, e.g. social media posts. An LLM predicts the probable order of combinations of words, a bit like the autocomplete function on a smartphone. Based on these probabilities, it can produce text outputs. LLM chatbots run on servers with huge amounts of computing power that people have built in data centres around the world.<\/p>\n

Our AI education resources for young people<\/strong><\/h2>\n

AI applications are often described as \u201cblack boxes\u201d or \u201cclosed boxes\u201d: they may be relatively easy to use, but it\u2019s not as easy to understand how they work. We believe that it\u2019s fundamentally important to help everyone, especially young people, to understand the potential of AI technologies and to open these closed boxes to understand how they actually work.<\/p>\n

As always, we want to demystify digital technology for young people, to empower them to be thoughtful creators of technology and to make informed choices about how they engage with technology \u2014 rather than just being passive consumers.<\/p>\n

That\u2019s the goal we have in mind as we\u2019re working on lesson resources<\/a> to help teachers and other educators introduce KS3 students (ages 11 to 14) to AI and ML. We will release these Experience AI lessons very soon.<\/p>\n

Why we avoid describing AI as human-like<\/strong><\/h2>\n

Our researchers at the Raspberry Pi Computing Education Research Centre<\/a> have started investigating the topic of AI and ML, including thinking deeply about how AI and ML applications are described to educators and learners.<\/p>\n

To support learners to form accurate mental models of AI and ML, we believe it is important to avoid using words that can lead to learners developing misconceptions around machines being human-like in their abilities. That\u2019s why \u2018anthropomorphism\u2019 is a term that comes up regularly in our conversations about the Experience AI lessons we are developing.<\/p>\n

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To anthropomorphise<\/strong>: \u201cto show or treat an animal, god, or object<\/strong> as if it is human in appearance, character, or behaviour\u201d<\/p>\n

https:\/\/dictionary.cambridge.org\/dictionary\/english\/anthropomorphize<\/em><\/cite><\/p><\/blockquote>\n

Anthropomorphising AI in teaching materials might lead to learners believing that there is sentience or intention within AI applications. That misconception would distract learners from the fact that it is people who design AI applications and decide how they are used. It also risks reducing learners\u2019 desire to take an active role in understanding AI applications, and in the design of future applications.<\/p>\n

Examples of how anthropomorphism is misleading<\/strong><\/h2>\n

Avoiding anthropomorphism helps young people to open the closed box of AI applications. Take the example of a smart speaker. It\u2019s easy to describe a smart speaker\u2019s functionality in anthropomorphic terms such as \u201cit listens\u201d or \u201cit understands\u201d. However, we think it\u2019s more accurate and empowering to explain smart speakers as systems developed by people to process sound and carry out specific tasks. Rather than telling young people that a smart speaker \u201clistens\u201d and \u201cunderstands\u201d, it\u2019s more accurate to say that the speaker receives input, processes the data, and produces an output. This language helps to distinguish how the device actually works from the illusion of a persona the speaker\u2019s voice might conjure for learners.<\/p>\n

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Image: David Man & Tristan Ferne \/ Better Images of AI<\/a> \/ Trees \/ CC BY 4.0<\/a><\/figcaption><\/figure>\n<\/div>\n

Another example is the use of AI in computer vision. ML models can, for example, be trained to identify when there is a dog or a cat in an image. An accurate ML model, on the surface, displays human-like behaviour. However, the model operates very differently to how a human might identify animals in images. Where humans would point to features such as whiskers and ear shapes, ML models process pixels in images to make predictions based on probabilities.<\/p>\n

Better ways to describe AI<\/strong><\/h2>\n

The Experience AI lesson resources we are developing introduce students to AI applications and teach them about the ML models that are used to power them. We have put a lot of work into thinking about the language we use in the lessons and the impact it might have on the emerging mental models of the young people (and their teachers) who will be engaging with our resources.<\/p>\n

It\u2019s not easy to avoid anthropomorphism while talking about AI, especially considering the industry standard language in the area: artificial intelligence<\/em>, machine learning<\/em>, computer vision,<\/em> to name but a few examples. At the Foundation, we are still training ourselves not to anthropomorphise AI, and we take a little bit of pleasure in picking each other up on the odd slip-up.<\/p>\n

Here are some suggestions to help you describe AI better:<\/p>\n

\n\n\n\n\n\n\n
Avoid using<\/strong><\/td>\nInstead use<\/strong><\/td>\n<\/tr>\n
Avoid using phrases such as \u201cAI learns<\/em>\u201d or \u201cAI\/ML does\u201d<\/em><\/td>\nUse phrases such as \u201cAI applications are designed to\u2026<\/em>\u201d or \u201cAI developers build applications that\u2026<\/em>\u201d<\/td>\n<\/tr>\n
Avoid words that describe the behaviour of people (e.g. see, look, recognise, create, make<\/em>)<\/td>\nUse system type words (e.g. detect, input, pattern match, generate, produce<\/em>)<\/td>\n<\/tr>\n
Avoid using AI\/ML as a countable noun, e.g. \u201cnew artificial intelligences emerged in 2022\u201d<\/em><\/td>\nRefer to \u2018AI\/ML\u2019 as a scientific discipline, similarly to how you use the term \u201cbiology\u201d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

The purpose of our AI education resources<\/strong><\/h2>\n

If we are correct in our approach, then whether or not the young people who engage in Experience AI grow up to become AI developers, we will have helped them to become discerning users of AI technologies and to be more likely to see such products for what they are: data-driven applications and not sentient machines.<\/p>\n

If you want to use the Experience AI lessons to teach your learners, please sign up to be the first to hear<\/a> when we launch these resources.<\/p>\n

The post How anthropomorphism hinders AI education<\/a> appeared first on Raspberry Pi Foundation<\/a>.<\/p>\n


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In the 1950s, Alan Turing explored the central question of artificial intelligence (AI). He thought that the original question, \u201cCan machines think?\u201d, would not provide useful answers because the terms \u201cmachine\u201d and \u201cthink\u201d are hard to define. Instead, he proposed … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":1128307,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"ngg_post_thumbnail":0,"footnotes":""},"categories":[77,110],"tags":[5],"class_list":["post-1128306","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-rpi","category-unfiltered-rss","tag-rpi"],"_links":{"self":[{"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/posts\/1128306","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1128306"}],"version-history":[{"count":0,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/posts\/1128306\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=\/wp\/v2\/media\/1128307"}],"wp:attachment":[{"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1128306"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1128306"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.prime-wow.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1128306"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}