Ethics

Building responsible AI systems starts with recognizing that technology solutions implicitly prioritize efficiency.

In an era of complex ethics algorithms and DEI/CSP/ESG checklists, simpler is better.

Once leaders address their company’s historical transgressions, they can work to create a more positive legacy.

An empowered strategic integrity function is key to developing a more proactive and systemic approach to governance.

This issue of MIT SMR looks at corporate values and purpose, risk management, and the role of the CFO in acquisitions.

Reporting on unethical conduct in the workplace is linked to employees’ degree of psychological safety.

When we rely on machines to make decisions, we substitute data-driven calculations for human judgment.

Driving culture change with organizational network analysis, responding strategically to cyberattacks, and building human rights strategies.

When their operations intersect with labor or human rights abuses, companies need to have a plan of action at the ready.

Salesforce’s Paula Goldman discusses how the tech company produces value-creating solutions with ethics in mind.

To reduce ethical lapses, organizations need systems for anticipation and systems for resilience.

The pandemic’s impact on business strategy, digital superpowers to thrive through disruption, and “explicit uncertainty” to avoid algorithmic harm.

Robert Chesnut, Airbnb’s first chief ethics officer, shares his experience shaping ethical technology policies.

To address algorithms’ potential harm, companies must be willing to focus on users and rethink their business models.

Companies that manage employee data responsibly are better able to grow trust across the company while gaining insights.

A new article series explores how organizations must manage and monitor technology in new ways to achieve positive ethical outcomes.

This Strategy Guide shares insights on AI use for strategic advantage and positive societal impact.

Elizabeth Renieris of the Notre Dame-IBM Technology Ethics Lab discusses how businesses can responsibly govern AI projects.

Connecting through collaboration and conflict, preventing leader derailment, and assessing the impact of leaders’ unethical requests.

When leaders ask employees to cross ethical lines, they risk reducing workers’ long-term performance.