{"id":75989,"date":"2025-02-25T00:52:27","date_gmt":"2025-02-25T05:52:27","guid":{"rendered":"https:\/\/world.edu\/?p=75989"},"modified":"2025-02-25T13:14:12","modified_gmt":"2025-02-25T18:14:12","slug":"erotica-gore-and-racism-how-americas-war-on-ideological-bias-is-letting-ai-off-the-leash","status":"publish","type":"post","link":"https:\/\/world.edu\/erotica-gore-and-racism-how-americas-war-on-ideological-bias-is-letting-ai-off-the-leash\/","title":{"rendered":"Erotica, gore and racism: how America\u2019s war on \u2018ideological bias\u2019 is letting AI off the leash"},"content":{"rendered":"

\"\"<\/p>\n

Badly behaved artificial intelligence (AI) systems have a long history in science fiction. Way back in 1961, in the famous Astro Boy comics by Osamu Tezuka, a clone of a popular robot magician<\/a>\u00a0was reprogrammed into a super-powered thief. In the 1968 film 2001: A Space Odyssey, the shipboard computer\u00a0HAL 9000<\/a>\u00a0turns out to be more sinister than the astronauts on board think.<\/p>\n

More recently, real-world chatbots such as\u00a0Microsoft\u2019s Tay<\/a>\u00a0have shown that AI models \u201cgoing bad\u201d isn\u2019t sci-fi any longer. Tay started spewing racist and sexually explicit texts within hours of its public release in 2016.<\/p>\n

The generative AI models we\u2019ve been using since ChatGPT launched in November 2022 are generally well behaved. There are signs this may be about to change.<\/p>\n

On February 20, the US Federal Trade Commission announced\u00a0an inquiry<\/a>\u00a0to understand \u201chow consumers have been harmed [\u2026] by technology platforms that limit users\u2019 ability to share their ideas or affiliations freely and openly\u201d.\u00a0Introducing the inquiry<\/a>, the commission said platforms with internal processes to suppress unsafe content \u201cmay have violated the law\u201d.<\/p>\n

The latest version of the Elon Musk\u2013owned Grok model already serves up \u201cbased<\/a>\u201d opinions, and features an \u201cunhinged mode<\/a>\u201d that is \u201cintended to be objectionable, inappropriate, and offensive\u201d. Recent ChatGPT updates allow the bot to produce \u201cerotica and gore<\/a>\u201d.<\/p>\n

These developments come after moves by US President Donald Trump to deregulate AI systems. Trump\u2019s attempt to\u00a0remove \u201cideological bias\u201d from AI<\/a>\u00a0may see the return of rogue behaviour that AI developers have been working hard to suppress.<\/p>\n

Executive orders<\/strong><\/h4>\n

In January, Trump issued a sweeping\u00a0executive order<\/a>\u00a0against \u201cillegal and immoral discrimination programs, going by the name \u2018diversity, equity, and inclusion\u2019 (DEI)\u201d, and\u00a0another<\/a>\u00a0on \u201cremoving barriers to AI innovation\u201d (which includes \u201cengineered social agendas\u201d).<\/p>\n

In February, the US\u00a0refused<\/a>\u00a0to join 62 other nations in signing a \u201cStatement on Inclusive and Sustainable AI\u201d at the Paris AI Action Summit.<\/p>\n

What will this mean for the AI products we see around us? Some generative AI companies, including\u00a0Microsoft and Google<\/a>, are US federal government suppliers. These companies could come under significant direct pressure to eliminate measures to make AI systems safe, if the measures are perceived as supporting DEI or slowing innovation.<\/p>\n

AI developers\u2019 interpretation of the executive orders could result in AI safety teams being reduced in size or scope, or replaced by teams whose social agenda better aligns with Trump\u2019s.<\/p>\n

Why would that matter? Before generative AI algorithms are trained, they are neither helpful nor harmful. However, when they are fed a diet of human expression scraped from across the internet, their propensity to reflect biases and behaviours such as\u00a0racism<\/a>,\u00a0sexism<\/a>,\u00a0ableism<\/a>\u00a0and abusive language becomes clear.<\/p>\n

AI risks and how they\u2019re managed<\/strong><\/h4>\n

Major AI developers spend a lot of effort on suppressing biased outputs and unwanted model behaviours and rewarding more ethically neutral and balanced responses.<\/p>\n

Some of these measures could be seen as implementing DEI principles, even as they help to avoid incidents like the one involving Tay. They include the\u00a0use of human feedback to tune model outputs<\/a>, as well as monitoring and measuring bias towards specific populations.<\/p>\n

Another approach, developed by Anthropic for its Claude model, uses a\u00a0policy document called a \u201cconstitution\u201d<\/a>\u00a0to explicitly direct the model to respect principles of harmless and respectful behaviour.<\/p>\n

Model outputs are often tested via \u201cred teaming\u201d. In this process, prompt engineers and internal AI safety experts do their best to provoke unsafe and offensive responses from generative AI models.<\/p>\n

A Microsoft\u00a0blog post<\/a>\u00a0from January described red teaming as \u201cthe first step in identifying potential harms [\u2026] to measure, manage, and govern AI risks for our customers\u201d.<\/p>\n

The risks span a \u201cwide range of vulnerabilities\u201d, \u201cincluding traditional security, responsible AI, and psychosocial harms\u201d.<\/p>\n

The blog also notes \u201cit is crucial to design red teaming probes that not only account for linguistic differences but also redefine harms in different political and cultural contexts\u201d. Many generative AI products have a global user base. So this sort of effort is important for making the products safe for consumers and businesses well beyond US borders.<\/p>\n

We may be about to relearn some lessons<\/strong><\/h4>\n

Unfortunately, none of these efforts to make generative AI models safe is a one-shot process. Once generative AI models are installed in chatbots or other apps, they continually digest information from the human world through prompts and other inputs.<\/p>\n

This diet can shift their behaviour for the worse over time. Malicious attacks, such as\u00a0user prompt injection<\/a>\u00a0and\u00a0data poisoning<\/a>, can produce more dramatic changes.<\/p>\n

Tech journalist Kevin Roose used prompt injection to make Microsoft Bing\u2019s AI chatbot\u00a0reveal its \u201cshadow self\u201d<\/a>. The upshot? It encouraged him to leave his wife.\u00a0Research published last month<\/a>\u00a0showed that a mere drop of poisoned data could make medical advice models generate misinformation.<\/p>\n

Constant monitoring and correction of AI outputs are essential. There is no other way to avoid offensive, discriminatory or unsafe behaviours cropping up without warning in generated responses.<\/p>\n

Yet all signs suggest the Trump administration favours a reduction in the ethical regulation of AI. The executive orders may be interpreted as allowing or encouraging the free expression and generation of even discriminatory and harmful views on subjects such as women, race, LGBTQIA+ individuals and immigrants.<\/p>\n

Generative AI moderation efforts may go the way of\u00a0Meta\u2019s fact-checking and expert content moderation programs<\/a>. This could have an impact on global users of US-made AI products such as OpenAI ChatGPT, Microsoft Co-Pilot and Google Gemini.<\/p>\n

We might be about to rediscover how essential these efforts have been to keep AI models in check.<\/p>\n

Author Bio:<\/strong> Judith Bishop is the Tracey Banivanua Mar Fellow at La Trobe University<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Badly behaved artificial intelligence (AI) systems have a long history in science fiction. Way back in 1961, in the famous Astro Boy comics by Osamu Tezuka, a clone of a popular robot magician\u00a0was reprogrammed into a super-powered thief. In the 1968 film 2001: A Space Odyssey, the shipboard computer\u00a0HAL 9000\u00a0turns out to be more sinister […]\n… learn more→<\/a><\/p>","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[435283],"coauthors":[11733],"class_list":["post-75989","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-ideological-bias"],"acf":[],"yoast_head":"\nErotica, gore and racism: how America\u2019s war on \u2018ideological bias\u2019 is letting AI off the leash - World leading higher education information and services<\/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:\/\/world.edu\/erotica-gore-and-racism-how-americas-war-on-ideological-bias-is-letting-ai-off-the-leash\/\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_US\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"Erotica, gore and racism: how America\u2019s war on \u2018ideological bias\u2019 is letting AI off the leash - World leading higher education information and services\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"Badly behaved artificial intelligence (AI) systems have a long history in science fiction. 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