Scientific Sense Podcast

Showing posts with label economics. technology. Show all posts
Showing posts with label economics. technology. Show all posts

Friday, November 10, 2023

Celina Lee, CEO of Zindi on the quest to increasing access to AI in Africa

Monday, April 5, 2021

Scientific Sense ® Podcast with Gill Eapen: Most popular episodes in Social Sciences.

 Scientific Sense ® Podcast with Gill Eapen: Most popular episodes in Social Sciences.

1. Prof. Itay Goldstein of the University of Pennsylvania on Financial Markets.

2. Prof. Christopher Blattman of the University of Chicago on Crime.

3. Prof. Julia Lane of New York University on democratizing data.

4. Prof. David Uttal of Northwestern University on spatial thinking.

5. Prof. Erik Berglof of The London School of Economics and Political Science (LSE) on the global pandemic.

6. Prof. Carol Christine Fair of Georgetown University on militant politics.

7. Dr. Dipayan Ghosh of the Harvard Kennedy School on natural monopolies;

8. Prof. Mark Wilson of the University of Pittsburgh on the Imitation of Rigor

9. Prof. Jeff Ely of Northwestern University on Suspense and Surprise.

10. Dr. Fred Olayele, PhD of the New York City Economic Development Corporation on Economic Diversity.

#economics #policy #decisionoptions

Friday, September 6, 2019

The emerging Principal-Agent-Machine problem in the enterprise

Ever since the owners of organizations put agents in charge of operations, because of growing scale and perceived need for management specialization, shareholder value maximization has not been Pareto optimal for decision-makers. Much has been written and studied in this area with little effect on organizational structure, systems, and strategies (1). From the advent of computers, agents have been effective in claiming superiority over machines because of a lack of transparency for the owners. Although it is difficult to prove that machines possess superior decision-making capabilities in real companies and markets because of the lack of data from long and repeated experiments, it is clearly the case in financial markets.

With clear and consistent data in the financial markets, it has long been clear that financial intermediaries and traders have been destroying alpha, forever. With misguided and a confusing focus on "absolute returns," these agents have been successful in siphoning out wealth from owners in fees and expenses. An illustrious investment bank seems to have recently recognized that "trading," done by humans creates no value for its clients. Machines are infinitely better as they can act based on complete information without bias. Decision-making, thus, is better delegated to machines.

In real markets, this is equally applicable. Because of high diversity in types of decisions and long durations to outcomes, agents have long claimed superior capabilities compared to machines. This is true at all levels of organizations (1) and in every function. Since distributed owners are unable to understand the inner workings of complex organizations, agents simply claimed they are better without any contention. This has significant negative effects on the economy and its potential to grow. A structural change that culminates in the reassignment of human responsibilities in the enterprise may be afoot.

The emerging principal-agent-machine problem is real for modern organizations. Institutionalization of agents since the industrial revolution has run its course. Owners may finally have an opportunity to break this stalemate.