Ernest Chaney’s Post

AI Ethics: A Team Approach for Success 🙌 The role of #AI Ethicist is becoming a hot topic as businesses grow more reliant on AI. The ethical issues that arise from AI are complex and multi-dimensional, requiring expertise across a wide range of disciplines. Companies should take a team approach to AI ethics, achieving the required multi-disciplinary capabilities and experience. AI ethics in a business context can’t just be a philosophical exercise. Policies, frameworks, and other guidance related to AI ethics need to be usable in the real world. What steps is your company taking to address the #ethical issues arising from AI? https://buff.ly/4bBwetw #Ethics #Innovation #Trend #Foresight #BusinessStrategy #Strategy #Management

Implementing AI Ethics in Business Strategy

AI ethics is a widely discussed topic. Here is a good article to value AI ethics for businesses.

Successful AI Ethics & Governance at Scale: Bridging The Organizational and Implementation Gaps https://ift.tt/q6YBKlb The Road From Ethics to Executives Winds Through Lawyers and LLMs Designed by Freepik When it comes to AI governance, what do the world’s largest AI companies, the world’s smartest AI academics, and the world’s most famous consulting firms have in common? None of them are responsible for actually making it work in your company. This is part 2 of a series on successful implementing AI ethics and governance in large organizations. Part 1 talks about the challenge of interpretation: how specialist talent is needed to bridge the gap between high level policies and unique AI use cases. In this article we talk about the next two gaps: the organizational gap looking at the challenge of AI ethics and governance ownership spread across different departments, and the implementation gap of reluctance to implement scaled AI ethics and governance measures under pressure to adopt AI. The focus is on AI ethics and governance at scale — in a way that is embedded in the core processes and decisions of the company. Starting on AI ethics is easy — the problem is they often end with the 3 Ps of principles, pilots and PR (public relations). Munn (2022)’s provocative paper ‘The Uselessness of AI Ethics’ encapsulates this well: The failure of AI ethical principles is not spectacular but silent, resulting in the desired outcome: business as usual. With that, let’s jump in. The Organizational Gap In AI Ethics and Governance: Multidisciplinary Collaboration is Hard The evolving AI landscape presents unique challenges in aligning AI ethics and governance with existing organizational structures. Spoiler: There isn’t much alignment out of the box — it is a new set of skills which will likely spawn a new function, but today is distributed across multiple teams. Until this is solved, there will be a dissonance between theoretical frameworks of AI ethics and how it plays out practically when it comes to ownership, funding and decision rights. Many teams have a stake in it, but by that same fact few teams grasp its full scope. Every team brings its own lens to AI ethics and governance, and each has a high-resolution view of their own part of the puzzle, and a low-resolution view of other teams which are incomplete at best and assumption-filled caricatures at worst. Such misalignments lead to organizational tension, resulting from differing perspectives and levels of understanding among various stakeholders. Drivers of this gap include: AI Ethics and Governance Capabilities Operating in Organizational Silos Any implementation effort attempting to solve AI ethics and governance needs to overcome the siloed nature of organizations. Different departments such as data science, cybersecurity, and compliance often operate independently, leading to a fragmented approach to AI ethics. These departments also have multiple sub-teams, compounding...

Interesting article on the ethics in AI.

🔎Exploring the critical juncture of Artificial Intelligence and Information Ethics. In today's digital realm, understanding the ethical dimensions is vital. ⚖️At CreativCollectivX, we embrace AI's transformative tools while upholding the responsibility they entail. Dive into the nuanced realm where ownership, creator dignity, and information integrity converge.  . . . #AI #informationethics #brandbuilding #marketingagency #socialmediamarketing

Successful AI Ethics & Governance at Scale: Bridging The Organizational and Implementation Gaps The Road From Ethics to Executives Winds Through Lawyers and LLMs Designed by Freepik When it comes to AI governance, what do the world’s largest AI companies, the world’s smartest AI academics, and the world’s most famous consulting firms have in common? None of them are responsible for actually making it work in your company. This is part 2 of a series on successful implementing AI ethics and governance in large organizations. Part 1 talks about the challenge of interpretation: how specialist talent is needed to bridge the gap between high level policies and unique AI use cases. In this article we talk about the next two gaps: the organizational gap looking at the challenge of AI ethics and governance ownership spread across different departments, and the implementation gap of reluctance to implement scaled AI ethics and governance measures under pressure to adopt AI. The focus is on AI ethics and governance at scale — in a way that is embedded in the core processes and decisions of the company. Starting on AI ethics is easy — the problem is they often end with the 3 Ps of principles, pilots and PR (public relations). Munn (2022)’s provocative paper ‘The Uselessness of AI Ethics’ encapsulates this well: The failure of AI ethical principles is not spectacular but silent, resulting in the desired outcome: business as usual. With that, let’s jump in. The Organizational Gap In AI Ethics and Governance: Multidisciplinary Collaboration is Hard The evolving AI landscape presents unique challenges in aligning AI ethics and governance with existing organizational structures. Spoiler: There isn’t much alignment out of the box — it is a new set of skills which will likely spawn a new function, but today is distributed across multiple teams. Until this is solved, there will be a dissonance between theoretical frameworks of AI ethics and how it plays out practically when it comes to ownership, funding and decision rights. Many teams have a stake in it, but by that same fact few teams grasp its full scope. Every team brings its own lens to AI ethics and governance, and each has a high-resolution view of their own part of the puzzle, and a low-resolution view of other teams which are incomplete at best and assumption-filled caricatures at worst. Such misalignments lead to organizational tension, resulting from differing perspectives and levels of understanding among various stakeholders. Drivers of this gap include: AI Ethics and Governance Capabilities Operating in Organizational Silos Any implementation effort attempting to solve AI ethics and governance needs to overcome the siloed nature of organizations. Different departments such as data science, cybersecurity, and compliance often operate independently, leading to a fragmented approach to AI ethics. These departments also have multiple sub-teams, compounding the issue. For all the...

⚫AI ethics should not be viewed as separate from information ethics but rather as a continuation of the same core principles. In this article, find out our stance. What’s yours❓ 📖 https://lnkd.in/d5u4hEQS #expertconsultancy #AIethics #informationethics #CohesionX #harmonyinexpertise

🌟 Exciting News in the World of AI Ethics! 🌟 Thrilled to share the success of the recent thought-provoking discussion on AI ethics hosted at the University of Geneva. Esteemed speakers like @KaiZenner, @CaroRobson, @GiuseppeUgazio, @IlonaMaklakova, @RuggeroHuesler, and expert moderator Jean-Marc Seigneur led captivating conversations on the critical topic of ethical AI development. The event highlighted key ethical considerations in AI, including algorithmic bias, privacy protection, transparency, and human-centric design. It emphasized the importance of ethical governance and collaboration to ensure AI technologies align with fundamental ethical principles for the betterment of humanity. Kudos to the sponsors who played a pivotal role in making this event a success and fostering dialogue around ethical AI development. Let's continue to advance ethical AI by fostering collaboration, promoting governance frameworks, enhancing public understanding, investing in research, and nurturing ethical AI talent. Excited to see how these discussions will shape the future of AI technology for the greater good of society. Together, let's embark on this vital journey guided by shared values and a deep commitment to the world of AI ethics. 💡✨ Check out the full event recap here: https://lnkd.in/dva6Dxmd #AI #Ethics #UniversityOfGeneva #ThoughtLeadership #AIforGood #GlobalAIAssociation #TechEthics #FutureTech #InnovationEthics

Medium Why every AI startup should hire a Head of AI Ethics on Day 1