{"id":22435,"date":"2025-01-24T15:33:18","date_gmt":"2025-01-24T15:33:18","guid":{"rendered":"https:\/\/interface.media\/?p=22435"},"modified":"2025-01-24T15:33:24","modified_gmt":"2025-01-24T15:33:24","slug":"what-will-it-take-to-achieve-socially-responsible-ai","status":"publish","type":"post","link":"https:\/\/interface.media\/blog\/2025\/01\/24\/what-will-it-take-to-achieve-socially-responsible-ai\/","title":{"rendered":"What will it take to achieve socially responsible AI?"},"content":{"rendered":"\n

As artificial intelligence (AI) continues to reshape industries \u2013 driving business innovation, altering the labour market, and enhancing productivity \u2013 organisations are rushing to implement AI technologies across workflows. However, while doing so, they should avoid overlooking the need for reliability<\/a>. It\u2019s crucial to avoid the temptation of adopting AI quickly without ensuring its output is rooted in trusted and accurate data.<\/p>\n\n\n\n

For 16 years, Stack Overflow has empowered developers as the go-to platform to ask questions and share knowledge with fellow technologists. Today, we are harnessing that history to address the urgent need to develop ethical AI<\/a>.\u00a0<\/p>\n\n\n\n

In setting a new standard for trusted and accurate data to be foundational in how we collectively build and deliver AI solutions to users, we want to create a future where people can use AI ethically and successfully. With many generative AI systems susceptible to hallucinations and misinformation, ensuring socially responsible AI is more critical than ever.<\/p>\n\n\n\n

The Role of Community and Data Quality<\/h3>\n\n\n\n

The foundation of responsible AI lies in the quality of the data used to train it. High-quality data is the starting point for any ethical AI initiative. Fortunately, Stack Exchange Communities has built an enormous archive of reliable information from our developer community. <\/p>\n\n\n\n

With over a decade and a half of community-driven knowledge, including more than 58 million questions and answers, our platform provides a wealth of trusted, human-validated data that AI developers can used to train large language models (LLMs).<\/p>\n\n\n\n

However, it\u2019s not only the amount of data available but how it is used. Socially responsible use<\/a> of community data must be mutually beneficial, with AI partners giving back to the communities they rely on. Our partners who contribute to community development gain access to more content, while those who don\u2019t risk losing the trust of their users going forward. <\/p>\n\n\n\n

A Partnership Built on Responsibility<\/h3>\n\n\n\n

Our AI partner policy is rooted in a commitment to transparency, trust, and proper attribution. Any AI product or model that utilises Stack Overflow\u2019s public data must attribute its insights back to the original posts that contributed to the model\u2019s output. By crediting the subject matter experts and community members who have taken an active role in curating this information, we deliver a higher level of accountability.<\/p>\n\n\n\n

Our annual Developer Survey of over 65,000 developers found that 65% of respondents are concerned about missing or incorrect attribution from data sources. Maintaining a higher level of transparency is critical to building a foundation of trust. Additionally, the licensed use of human-curated data can help companies reduce legal risk. Responsible use of AI and attribution isn\u2019t just a question of ethics but a matter of increased legal and compliance risk for organisations. <\/p>\n\n\n\n

Ensuring Accurate and Up-to-Date Content<\/h3>\n\n\n\n

It\u2019s important that AI models draw from the most current and accurate information available to keep them relevant and safe to use. <\/p>\n\n\n\n

While 76% of our Developer Survey respondents reveal they are currently using or planning to use AI tools, only 43% trust the accuracy of their outputs. On Stack Overflow\u2019s public platform, a human moderator reviews both AI-assisted and human-submitted questions before publication. This step of human review provides an additional and necessary layer of trust.\u00a0<\/p>\n\n\n\n

This human-in-the-loop approach not only maintains the accuracy and relevance of the information but also ensures that patterns are identified and additional context is applied when necessary. Furthermore, encouraging AI systems to interact directly with our community enables continuous model refinement and revalidation of our data.<\/p>\n\n\n\n

The Importance of the Two-Way Feedback Loop<\/h3>\n\n\n\n

Transparency and continuous improvement are central to responsible AI development. A robust two-way communication loop between users and AI is critical for advancing the technology. In fact, 66% of developers express concerns about trusting AI\u2019s outputs, making this feedback loop essential for maintaining confidence in the output of AI systems. <\/p>\n\n\n\n

Feedback from users informs improvements to models, which in turn helps to improve quality and reliability.<\/p>\n\n\n\n

That\u2019s why it\u2019s vital to acknowledge and credit the community platforms that power AI systems. Without maintaining these feedback loops, we lose the opportunity for growth and innovation in our knowledge communities. <\/p>\n\n\n\n

Strength in Community Collaboration<\/h3>\n\n\n\n

At the core of successful and ethical AI use is community collaboration. Our mission is to bring together developers’ ingenuity, AI’s capabilities, and the tech community’s collective knowledge to solve problems, save time, and foster innovation in building the technology and products of the future. <\/p>\n\n\n\n

We believe the synergy between human expertise and technology will drive the future of socially responsible AI. At Stack Overflow, we are proud to lead this effort, collaborating with our API partners to push the boundaries of AI while staying committed to socially responsible practices.<\/p>\n","protected":false},"excerpt":{"rendered":"

Ellen Brandenberger, Senior Director of Product Innovation at Stack Overflow, asks whether it\u2019s possible to implement AI ethically. <\/p>\n","protected":false},"author":480,"featured_media":22436,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"apple_news_api_created_at":"2025-01-24T15:33:23Z","apple_news_api_id":"aab62cd3-4087-4cb4-968c-628ad12de9c2","apple_news_api_modified_at":"2025-01-24T15:33:23Z","apple_news_api_revision":"AAAAAAAAAAD\/\/\/\/\/\/\/\/\/\/w==","apple_news_api_share_url":"https:\/\/apple.news\/AqrYs00CHTLSWjGKK0S3pwg","apple_news_cover_media_provider":"image","apple_news_coverimage":0,"apple_news_coverimage_caption":"","apple_news_cover_video_id":0,"apple_news_cover_video_url":"","apple_news_cover_embedwebvideo_url":"","apple_news_is_hidden":"","apple_news_is_paid":"","apple_news_is_preview":"","apple_news_is_sponsored":"","apple_news_maturity_rating":"","apple_news_metadata":"\"\"","apple_news_pullquote":"","apple_news_pullquote_position":"","apple_news_slug":"","apple_news_sections":[],"apple_news_suppress_video_url":false,"apple_news_use_image_component":false,"footnotes":""},"categories":[3],"tags":[],"topic":[614],"class_list":["post-22435","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-the-interface","topic-data-ai"],"acf":[],"apple_news_notices":[],"yoast_head":"\nWhat will it take to achieve socially responsible AI? 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