Workplace AI ownership debate: Advocating for shared responsibility
In the rapidly evolving world of artificial intelligence (AI), the question of who owns AI at work is less significant than what AI should be used for: enhancing human capability and creating value. Recent research by Culture Amp into Inc. 5000 organizations underscores the importance of diverse stewardship in high-performing companies, as they invest in people and AI infrastructure that supports performance both now and in the future.
The success of AI in Human Resources (HR) necessitates stewards who understand both human dynamics and technical possibilities. With AI's impact being inherently cross-functional, affecting areas such as ethical considerations in hiring algorithms, operational efficiency, employee engagement, and performance coaching, a cross-functional AI working group can ensure solutions are technically sound while also aligning with the company's needs, values, and ethical practices.
This diverse group, spanning multiple levels and roles, is essential for optimal AI stewardship in organizations. Key participants include C-suite executives, legal and compliance officers, ethics officers or committees, data scientists, AI product owners, technical stewards, operational leaders, frontline users, cross-departmental representatives, and specialized stewardship roles or councils.
This distributed stewardship model fosters collaboration, transparency, and trust, enabling AI to augment rather than replace human judgment and enhance organizational performance holistically. Real-world stewardship also involves ongoing bias audits, data governance, anomaly detection, and human-in-the-loop decision-making to maintain ethical and high-quality AI models over time.
Successful stewardship depends on shared responsibility from leadership down to frontline staff. Including compliance executives early and coordinating meticulously across stakeholders supports adaptive governance and equitable AI adoption. External collaborations with legal, academic, and sector-specific organizations can also provide trusted guidance and evaluation frameworks.
In summary, stewardship is a multidisciplinary, multi-level collaboration combining strategic, technical, legal, ethical, and operational expertise with local trusted relationships to ensure AI enhances both human and organizational performance effectively and equitably. For AI to succeed, it needs buy-in and understanding from leaders across the company.
[1] Culture Amp (2021). The Future of Work: 2021 Culture First Report. Retrieved from https://www.cultureamp.com/resources/future-of-work/ [2] MIT Sloan Management Review (2021). AI and the Ethics of Decision-Making. Retrieved from https://sloanreview.mit.edu/projects/ai-and-the-ethics-of-decision-making/ [3] Deloitte (2020). AI Ethics: Transforming AI from a risk into an asset. Retrieved from https://www2.deloitte.com/us/en/insights/topics/technology/artificial-intelligence/ai-ethics-transforming-ai-from-a-risk-into-an-asset.html [4] McKinsey & Company (2020). AI in the enterprise: Realizing value. Retrieved from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/ai-in-the-enterprise-realizing-value [5] World Economic Forum (2021). AI in the Workforce: A New Social Contract. Retrieved from https://www.weforum.org/reports/ai-in-the-workforce-a-new-social-contract
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