7 Pieces Highlighting the Potential Intersections of Machine Learning, AI, and Robotics with Behavioral Economics
The intersections of behavioral economics and increasingly popular fields and disciplines in technology, such as machine learning, artificial intelligence, and robotics, are still in their relative infancy. These seven articles, papers, and videos present interesting questions and findings that could act as launching points for potential interdisciplinary research. Be sure to check out the included Twitter/YouTube accounts and websites included along with the articles for more!
1. Scaling Nudges with Machine Learning
by Chris Risdon (Behavioral Scientist) // Twitter: @chrisrisdon / @behscientist
(Image Credit: Behavioral Scientist)
“It’s worth thinking about why machine learning could be extremely valuable—and maybe even necessary—when nudging for good. Thanks to technology, we are moving from an age in which products and services connect us to and better manage our things (music, money, email, friends) to an age in which products and services are explicitly designed to help us achieve behavior-based goals.”
2. Why Machine Learning and Big Data need Behavioral Economics
by Dr. Colin W. P. Lewis (www.robotenomics.com/)
“Data analysis is complex and requires both human and machine’s working together. The data scientists with knowledge of the biases, heuristics and works on decisions under uncertainty that behavioral economics provide will likely offer far more knowledgeable analysis than those without behavioral economics reasoning.”
3. Human And Machine Intelligence
by Prof. Dilip Soman // Twitter: @dilipsoman Youtube: BE101x
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“What’s so human about humans that machines cannot replicate, or cannot replicate? […] A couple of hallmarks of human decision making: one is the idea of inconsistency or unpredictability. So, like I’ve mentioned a few times, our theories are stochastic. You give people the same data and often times they come back with different responses, either because the context is different or because they are in a different state.”
4. Why Humans find Faulty Robots more Likeable
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“”Our results showed that the participants liked the faulty robot significantly more than the flawless one. This finding confirms the Pratfall Effect, which states that people’s attractiveness increases when they make a mistake,” says Nicole Mirnig. “Specifically exploring erroneous instances of interaction could be useful to further refine the quality of human-robotic interaction.”
5. Bad bots do good: Random artificial intelligence helps people coordinate
by Matthew Hudson // Twitter: @SilverJacket
“Further analysis showed that bots’ slightly noisy behavior benefited the networks in part by setting an example for others. Some people also showed “noise,” by occasionally deciding to pick a color that conflicted with their neighbors. The noise level of bots influenced the noise level in people—even those several nodes away, suggesting a ripple effect.”
6. Robotic Nudges: The Ethics of Engineering a More Socially Just Human Being
by Jason Borenstein and Ron Arkin
“Human behavior can be nudged in countless ways as already existing tactics for doing so clearly illustrate. Yet would “robot nudges” be different ethically or in other important respects from current nudging tactics, and if so, to what degree?”
7. Humans and AI: Rivals or Romance?
by Terence Tse, Mark Esposito and Danny Goh
“But this all begs one question: If technological progress represents a comprehensive threat to humans, then why do we still have jobs left? In fact, many of us are still working, probably much harder than before.”