Thursday, April 25, 2024

g-f(2)2289 GenAI and the Human Factor: Why Discernment Matters


genioux Fact post by Fernando Machuca and Bard (Gemini)


Generative AI offers incredible potential, but harnessing its power responsibly requires a nuanced understanding of the human-AI relationship. The concept of "speed bumps", as introduced in the video, sheds light on how strategic interventions can enhance the effectiveness and accuracy of our collaboration with AI tools.

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"In the realm of generative AI, sometimes intentionally slowing down leads to better results, highlighting the importance of critical thinking alongside technological advancement." — Fernando Machuca and Bard (Gemini), April 25, 2024

genioux Foundational Fact

The seamless integration of generative AI tools into workflows necessitates a shift away from blind trust towards a collaborative model where "speed bumps" encourage thoughtful evaluation of AI outputs. This approach fosters a healthy balance between human judgment and the efficiency gains offered by AI technology.

The 10 Most Relevant genioux Facts

  1. Generative AI tools hold the potential to introduce hidden errors or inaccuracies.
  2. Simply having a "human-in-the-loop" isn't a guarantee of perfect results when working with AI outputs.
  3. The concept of "speed bumps" refers to intentionally introduced friction to improve the human-AI partnership.
  4. Speed bumps make users pause and critically assess AI-generated content.
  5. Adding labels, highlights, or prompts for further human review are examples of beneficial speed bumps.
  6. Thoughtfully designed speed bumps can improve both the accuracy and efficiency of working with AI outputs.
  7. Speed bumps encourage active human engagement, mitigating the risk of over-reliance on AI.
  8. The optimal speed bump design depends on the specific AI tool and the task at hand.
  9. Calibrated trust is essential - neither blind acceptance nor complete dismissal of AI is productive.
  10. Ongoing research can refine best practices for maximizing the benefits of human-AI collaboration.


The notion of speed bumps offers a valuable lens for understanding the evolving dynamic between humans and generative AI. By embracing thoughtful strategies to integrate AI into our work, we can unlock greater potential, accuracy, and ultimately, better outcomes.


The g-f GK Context

Want Better GenAI Results? Try Speed Bumps, MIT Sloan Management Review, YouTube channel, April 25, 2024.

Video Credits

Renée Richardson Gosline is an MIT senior lecturer and research scientist.

Abbie Lundberg is the editor in chief at MIT Sloan Management Review.

M. Shawn Read is the multimedia editor at MIT Sloan Management Review.

The g-f GK Article

Want Better GenAI Results? Try Speed Bumps, MIT Sloan Management Review, April 25, 2024.

  • In this short video, Renée Richardson Gosline shares research on how to get more accurate results from generative AI without sacrificing speed.
  • Generative AI has vast potential to augment our work, now and in the future, but there’s a very real danger of human workers ceding too much control to machines and becoming complacent about mistakes. Maintaining a “human in the loop” is often touted as the antidote to catching errors, but MIT senior lecturer and research scientist Renée Richardson Gosline says that people frequently overestimate their ability to find flaws in GenAI-produced content.

Classical Summary

This video, titled "Want Better GenAI Results? Try Speed Bumps," is about the interplay between human judgment and AI, specifically generative AI.

In the video, Dr. Renee Richardson Goling, a researcher who studies human-AI interaction, discusses how generative AI can introduce errors into our work. She argues that while it is common to believe that a human-in-the-loop approach is sufficient to ensure accuracy, there is more to consider.

Dr. Goling proposes the concept of introducing beneficial friction into the workflow to mitigate these errors. This friction can slow users down and make them think more critically about the AI-generated content. The video presents an experiment where researchers added labels and highlights to the AI-generated content to call attention to potential errors or areas requiring a second look. The results showed that users with some friction (medium friction condition) achieved the best results - they were able to complete the tasks more accurately and in less time than those who had no friction (control condition).

Overall, the video highlights the need for a responsible approach to using generative AI and suggests that introducing beneficial friction can be a useful strategy to improve accuracy.

Renée Richardson Gosline

Here's a summary of Renée Richardson Gosline, an MIT senior lecturer and research scientist, focusing on her key areas of expertise and professional activities:


  • Affiliation: Senior Lecturer in the Management Science group at the MIT Sloan School of Management. She is also the head of the Human-First AI group at MIT's Initiative on The Digital Economy.
  • Academic Background: Holds a B.A. in Sociology from Harvard University, an M.A. and Ph. D. in Sociology from Harvard University.

Research Focus

Dr. Gosline's work centers on the intersection of behavioral science, technology, and cognitive bias in human decision-making.  Her key areas of research include:

  • Human-AI Interactions: Investigating how people collaborate with and use AI systems. This includes identifying and mitigating the potential for algorithmic bias.
  • Cognitive Bias and Decision-making: Examining how cognitive biases can unconsciously influence judgment, particularly in technology-mediated environments.
  • Digital Transformation and Organizational Change: Exploring the impact of AI and emerging technologies on businesses and work, emphasizing the human element required for successful adaptation.

Publications and Influence

  • Authored/Co-authored: Numerous academic papers, articles, and book chapters on her areas of research.
  • Speaker: Provides insights on the interplay of humans and AI at conferences and in media outlets like The Wall Street Journal, The BBC, NPR, and Forbes.
  • Advisor: Works with organizations to develop responsible AI strategies and build awareness of potential biases.

Overall Impact

Dr. Gosline's work contributes to a deeper understanding of the complex relationship between humans and AI. Her research highlights the importance of responsible AI development, ethical considerations, and the need for humans to maintain critical thinking skills in a world of ever-increasing technological advancement.

For further information, these resources would be helpful:

Renée Richardson Gosline website:

MIT Initiative on the Digital Economy:

Abbie Lundberg






Certainly! Abbie Lundberg is the Editor in Chief at MIT Sloan Management Review (MIT SMR). With over 30 years of experience, she is a content strategist, writer, and professional speaker. Abbie's expertise lies in reporting and commenting on tech-enabled business strategy, leadership, transformation, and change.

Here are some key points about Abbie Lundberg:

1. Background and Experience:

  • Abbie leads MIT SMR's editorial strategy and oversees both print and digital operations.
  • She has expanded MIT SMR's influence as a digital-first, integrated media brand connecting leaders and managers worldwide with trends, systems, and theories that drive successful organizations.
  • Before joining MIT SMR, Abbie founded Lundberg Media in 2009, where she produced influential papers on tech-enabled business strategy and transformation.
  • She has also led numerous executive roundtables, webinars, and events in the U.S. and abroad.

2. Previous Roles:

  • Abbie served as the Editor in Chief at CIO, a leading source of trusted information for chief information officers (CIOs). During her tenure, CIO experienced significant growth and became one of IDG's flagship media brands.

3. Mission at MIT SMR:

  • Abbie's mission at MIT SMR is to arm business leaders with information that positively impacts their organizations, careers, employees, customers, trading partners, and the broader world.

4. Recent Appointment:

  • In August 2021, Abbie Lundberg was appointed as the next editor in chief of MIT SMR, bringing her wealth of experience to this influential publication¹[1] ²[2].

Abbie's dedication to bridging the gap between technology and business makes her a valuable voice in the ever-evolving landscape of management and transformation. 🌟📈🔍

Learn more about Abbie Lundberg and her insights by visiting her profile on MIT SMR: [Abbie Lundberg - MIT Sloan Management Review]( ¹[1][1].

Source: Conversation with Bing, 4/27/2024

(1) Abbie Lundberg - MIT Sloan Management Review.

(2) MIT Sloan Management Review names Abbie Lundberg its next editor in chief.

(3) Abbie Lundberg’s Profile | MIT Sloan Management Review Journalist ....

(4) Managing Through Uncertainty - MIT Sloan Management Review.

(5) undefined.

M. Shawn Read





M. Shawn Read, the multimedia editor at MIT Sloan Management Review, is a creative force shaping the intersection of business, technology, and media. Let's delve into the essence of his role and contributions:

1. Multimedia Expertise:

  • As the multimedia editor, Shawn Read orchestrates a symphony of visual and auditory elements. His canvas spans articles, videos, webinars, and more.
  • He crafts a seamless blend of text, graphics, and sound, enhancing the MIT SMR experience for readers and learners.

2. Visual Storytelling:

  • Shawn's artistry lies in visual storytelling. He weaves narratives through images, infographics, and video clips, making complex concepts accessible.
  • Whether it's a thought-provoking article or an enlightening webinar, Shawn's touch amplifies the impact.

3. Collaboration and Innovation:

  • Behind the scenes, Shawn collaborates with authors, researchers, and fellow editors. His mission: elevate content through multimedia.
  • He embraces innovation, exploring new formats and technologies to engage MIT SMR's global audience.

4. Impactful Content Delivery:

  • Shawn's work isn't just about aesthetics; it's about enhancing understanding. Visuals complement words, creating a holistic learning experience.
  • From data-driven visualizations to captivating video interviews, he ensures that MIT SMR's insights resonate.

5. Future-Proofing Knowledge:

  • In an era where attention spans waver, Shawn's multimedia magic captures minds. He bridges the gap between academia and practice.
  • His creations become knowledge artifacts, accessible to curious minds worldwide.

So, next time you explore MIT SMR's rich content, remember that behind every pixel and frame, Shawn Read weaves a tapestry of wisdom and inspiration! 🎨📽️🌟

Learn more about MIT SMR's multimedia endeavors: [How AI Changes Your Workforce]( ¹[1].

Source: Conversation with Bing, 4/27/2024

(1) How AI Changes Your Workforce - MIT Sloan Management Review.

(2) MIT Sloan Management Review - Spring 2020 (PDF).

(3) The MIT Sloan Management Review Series | Subjects | Wiley.

(4) Want Better GenAI Results? Try Speed Bumps - MIT Sloan Management Review.

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This genioux Fact post is classified as Breaking Knowledge which means: Insights for comprehending the forces molding our world and making sense of news and trends.

Type: Breaking Knowledge, Free Speech

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