Beyond the hype: Making AI responsibility a reality, (not a buzzword)
Firstly, I want to say “thank you” to @Mark Wilson for triggering this article with his post#: https://www.linkedin.com/posts/mark-lewis-8468567_generative-ai-webinar-series-top-tips-and-activity-7108762045277184001-vg30?utm_source=share&utm_medium=member_desktop .
This article is about #aIaccountability, part of the project AI AND Business of @Transforage TCA Ltd. As technology continues to advance rapidly, we must open honest conversations about emerging issues like Artificial intelligence and responsibility. I want to provide some information and perspective. Artificial intelligence accountability is an evolving space with lots of activities. Here’s a quick snapshot of where things stand:
· Defining accountability - A recent study examined determining responsibility for AI systems. It proposed viewing it in terms of answerability, authority recognition, interrogation of the system, and limiting its power. · Building accountability into AI - A framework from the U.S. Government Accountability Office aims to bake accountability into AI systems throughout their lifecycle - from design to deployment and monitoring. · AI guidelines for government - Conversations about guidelines for the public sector’s use of AI are happening globally. · Human versus robot responsibility - Debates continue about whether AI systems should be held to similar responsibility standards as humans. Or do we need new standards and expectations?
The work remains to do: translating research and high-level concepts into implementation, guidelines across industries and use cases, with particular consideration for ethical points that remain unanswered. More exploration into AI decision-making algorithms’ effects on human values needs to occur, as well as auditing them to understand the real-world impacts of implementation decisions made on AI platforms. Now is also the time to implement accounting, auditing and financial reporting rules working with AI. So, while promising progress is being made, critical questions around implementing accountability practices, ethics, and setting responsibility expectations remain. Addressing these complex issues will require ongoing collaboration between companies, technology leaders, policymakers, lawyers and researchers as AI becomes more ubiquitous.
· I’m happy to dig deeper into any part of this conversation. My goal is to provide a balanced perspective and advice that promotes the responsible deployment of AI. Please feel free to pick up my brain if you want a complementary conversation about AI, responsibility and implementation, and its impact on Business continuity.
Beyond the hype… something has been overlooked: integrating data quality management with ML and AI with AI and ML accountability. · Email me: firstname.lastname@example.org · Ping me through Private message on Linkedin · Call or text me here: +44 07566842322.
Have a great week ahead ( and try to avoid the hype, please)