What is the jagged AI frontier?
A working definition from MIT Sloan
jagged AI frontier (noun)
The nonintuitive strengths and weaknesses of AI performance relative to human performance, and how it is changing over time.
A study about the impact of AI on the productivity of highly skilled workers sheds new light on the possibilities and pitfalls of relying too much on technology and not enough on human intuition.
A team of researchers that included MIT Sloan’s Kate Kellogg found that when generative AI is used within the boundary of its capabilities, it can improve a worker’s performance by as much as 40% compared with workers who don’t use it. But when generative AI is used outside that boundary in an attempt to complete a task, worker performance drops by an average of 19 percentage points.
Navigating this jagged technological frontier takes skill and training. Because some AI-generated answers look credible even when they’re incorrect, developers could work on designing an interface that would help workers avoid falling into such traps. Kellogg also recommended that organizations have an onboarding phase so employees can get a sense of how and where AI works well and where it doesn’t, and receive performance feedback. And everyone should be embracing a culture of accountability. “Managers and workers need to collectively develop new expectations and work practices to ensure that any work done in collaboration with generative AI meets the values, goals, and standards of their key stakeholders,” Kellogg said.
How generative AI can boost highly skilled workers’ productivity
Working Definitions: Artificial Intelligence
MIT Sloan's Working Definitions explore the words and phrases behind emerging management ideas.
Leading the AI-Driven Organization
In person at MIT Sloan
Register Now
The 5 forces creating urgency around ethical AI adoption
In his book “Boundaries of Tolerance,” MIT Sloan School of Management senior lecturer Jeffrey Saviano argues that ethical AI strategy and governance are the defining leadership challenges of our time.
Stop debating automation vs. augmentation
As organizations begin deploying agentic systems that can execute entire workflows, a consequential question is emerging: How can leaders turn agentic AI productivity gains into business growth?
How to level up systematic innovation with AI
Artificial intelligence can boost the systematic innovation of products, processes, and services. MIT Sloan professor Steven Eppinger offers four steps for making that happen.
AI and jobs: 4 takeaways from Google’s chief economist
Google’s Fabien Curto Millet examined how AI is reshaping job roles, workflows, and employee training in an address at the MIT Stone Center on Inequality and Shaping the Future of Work.
5 things to know about how companies can create value from AI
As AI tools become more widely available, competitive advantage will depend on the trust, data, expertise, operating capabilities, and work redesign companies build around them.
These new MIT Sloan courses track emerging technologies and business trends
MIT Sloan School of Management course offerings like AI-Augmented Work, Defense and Dual-Use Ventures, and Leading Agentic AI Transformation in Organizations anticipate businesses’ future needs.
‘The Collision: What AI Does to Us’
In his new book, MIT Sloan School of Management professor Eric So examines the ways AI is reshaping human cognition and offers advice on protecting your uniquely human skills while using AI.
4 seats AI can occupy at the negotiating table
AI can negotiate for you, coach you, support your team, or mediate between parties. An MIT Sloan School of Management professor explains those four roles — and why human judgment still matters.
Lessons from Kaiser Permanente’s AI labor deal
An MIT report details how Kaiser Permanente and the Alliance of Health Care Unions reached a landmark labor agreement to incorporate worker input into AI decision-making.
A framework for determining when AI can make decisions
The AI Decision Matrix uses ambiguity and risk to determine the optimal decision-making structure between humans and AI automation.