g-f(2)2074 Navigating the AI Frontier: Strategies for Measuring and Managing Organizational Impact

 

genioux Fact post by Fernando Machuca and Claude

Introduction:

In this bonus episode of "Me, Myself, and AI," a panel of experts from diverse backgrounds, including Olivia Bsk Curry from Amazon Web Services, Nicholas Solis from the U.S. Census Bureau, Carol Corrado from Georgetown University, and Scott Walston from the Technology Policy Institute, discuss the challenges and opportunities of measuring and managing the impact of artificial intelligence (AI) within organizations. The panelists explore issues such as defining AI use, barriers to adoption, the need for transparency, and the potential impacts on the workforce.

genioux GK Nugget:

"Effective measurement and management of AI's impact on organizations require a nuanced understanding of its varied applications, a focus on transparency and explainability, and a balanced approach to regulation that considers both risks and benefits." — Fernando Machuca and Claude

genioux Foundational Fact:

While AI adoption is increasing, organizations face challenges in defining and measuring AI use, as it often occurs incidentally through outsourced processes or employee-driven initiatives. Addressing these challenges requires a deeper understanding of AI's impact on firms, workers, and society, as well as a thoughtful approach to regulation that goes beyond catastrophizing worst-case scenarios.

10 genioux Facts:

1. A survey found that 56% of office workers and nearly 90% of marketing professionals have used AI, primarily generative AI, in their work.
2. Defining and measuring AI use is complex, as it can be a core business process or an incidental part of outsourced functions.
3. Cloud service providers can more easily measure AI usage through metrics like compute and storage consumption.
4. Explainable AI tools, such as those developed by IBM, help decision-makers understand the reasoning behind AI-generated options, promoting accountability and trust.
5. Transparency in AI should focus on providing users with the information they need to trust the output, such as citations and references.
6. Regulation of AI should be nuanced and consider the costs and benefits, rather than solely focusing on worst-case scenarios.
7. AI's impact on the workforce is not yet fully understood, with most firms reporting no change in worker composition after AI adoption.
8. When AI does impact the workforce, it is more likely to lead to hiring and upskilling rather than job losses.
9. Generative AI has the potential to automate tasks like responding to government requests for comments, necessitating the use of AI to process the increased volume of responses.
10. Public perception of AI tends to oscillate between extremes of hype and fear, lacking a balanced middle ground.

Real-world example:

IBM has developed a suite of explainable AI tools, such as IBM Watson OpenScale and IBM Watson Studio, which provide insights into how AI models make decisions. These tools help organizations build trust in AI systems by offering transparency and accountability, enabling users to understand the factors influencing AI-generated outputs and ensuring that the models align with business goals and ethical standards.

Conclusion:

As organizations increasingly adopt AI, it is crucial to develop a more nuanced understanding of its impact on firms, workers, and society. Failure to effectively measure and manage AI's impact can lead to unintended consequences, such as biased decision-making, job displacement, or erosion of public trust. By focusing on transparency, explainability, and balanced regulation, organizations can harness the benefits of AI while mitigating potential risks. Further research and dialogue are necessary to inform evidence-based policies and practices that promote the responsible and effective use of AI in organizations.

REFERENCE

The g-f GK Video

Bonus Episode: How Can Organizations Better Measure and Manage Artificial Intelligence?, MIT Sloan Management Review, YouTube channel, March 12, 2024.

MIT SMR description:

Me, Myself, and AI

On this bonus episode, we head to the World Bank offices in Washington, D.C., where hosts Sam and Shervin joined organizers Jonathan Timmis and Timothy DeStefano from the World Bank and Georgetown University’s McDonough School of Business for the day-long conference, “How is Artificial Intelligence Transforming Firms?” in December 2023.

In our final of three bonus episodes derived from this event, we explore how AI has shifted policy discussions, and what new types of management are needed.

This episode offers an abridged listen to the panel discussion; for the full session video, please visit the conference’s website.

"Me, Myself, and AI" Collaborative Podcast

"Me, Myself, and AI" is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group⁶. The podcast is hosted by Sam Ransbotham and Shervin Khodabandeh and aims to explore why only 10% of companies succeed with AI⁶. The hosts engage in conversations with people who are achieving significant wins with AI, sharing their stories to inspire others in their AI journeys⁶. The podcast covers a wide range of topics, from the practical applications of AI in various industries to the broader societal implications of AI³. It is available on all major podcast platforms³.

Source: Conversation with Bing, 3/13/2024

(1) undefined. https://podcasts.apple.com/us/podcast/me-myself-and-ai/id1533115958.

(2) Me, Myself, and AI - MIT Sloan Management Review. https://sloanreview.mit.edu/audio-series/me-myself-and-ai/.

(3) Me, Myself & AI - Shake & Stir. https://shakeandstir.com.au/education/for-teachers/in-school-shows/me-myself-and-a-i.

(4) . https://bing.com/search?q=Me%2c+Myself%2c+and+AI+summary.

(5) Me, Myself, and AI | STANFORD magazine. https://stanfordmag.org/contents/me-myself-and-ai.

(6) Me, myself and AI | DeepMind: The Podcast - Audible.com. https://www.audible.com/podcast/Me-myself-and-AI/B09T3FBY6K.

(7) undefined. https://www.memyselfinmind.com/.

(8) undefined. https://www.quora.com/When-was-the-phrase-me-myself-and-I-first-used.

(9) undefined. https://www.quora.com/What-does-me-myself-and-I-imply-I-mean-the-three-words-mean-the-same-so-what-is-the-implicit-meaning.

Claude's Summary:

In the bonus episode of "Me, Myself, and AI," a panel of experts convenes to discuss the challenges and opportunities organizations face when measuring and managing the impact of artificial intelligence (AI). The panelists include Olivia Bsk Curry, who leads political and Congressional affairs for Amazon Web Services; Nicholas Solis, a senior economist at the U.S. Census Bureau; Carol Corrado, a senior policy scholar at Georgetown University; and Scott Walston, president of the Technology Policy Institute.

The discussion begins by addressing the barriers to AI adoption and the surprising prevalence of employee-driven AI use. A survey revealed that 56% of office workers and nearly 90% of marketing professionals have used AI, primarily generative AI, in their work. However, measuring AI use proves to be complex, as it can be a core business process or an incidental part of outsourced functions.

The panelists explore the role of cloud service providers in facilitating AI adoption and measurement, as they can track metrics like compute and storage consumption. They also discuss the importance of explainable AI tools, which help decision-makers understand the reasoning behind AI-generated options, promoting accountability and trust.

Transparency in AI is another key topic, with the panelists emphasizing the need to provide users with the information they need to trust the output, such as citations and references. They also highlight the importance of nuanced regulation that considers the costs and benefits of AI, rather than focusing solely on worst-case scenarios.

The impact of AI on the workforce is also examined, with most firms reporting no change in worker composition after AI adoption. When AI does affect the workforce, it is more likely to lead to hiring and upskilling rather than job losses. The panelists note that generative AI has the potential to automate tasks like responding to government requests for comments, necessitating the use of AI to process the increased volume of responses.

Throughout the discussion, the panelists acknowledge that public perception of AI tends to oscillate between extremes of hype and fear, lacking a balanced middle ground. They emphasize the need for further research and dialogue to inform evidence-based policies and practices that promote the responsible and effective use of AI in organizations.

In conclusion, the panelists stress the importance of developing a more nuanced understanding of AI's impact on firms, workers, and society. By focusing on transparency, explainability, and balanced regulation, organizations can harness the benefits of AI while mitigating potential risks.

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Type: Bombshell Knowledge, Free Speech

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References

“genioux facts”: The online program on "MASTERING THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)2074, Fernando Machuca and Claude, March 12, 2024, Genioux.com Corporation.

 

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