Published By: New Scientist, 4/20/2017

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Summary

Michael Kahana and other researchers at the University of Pennsylvania have used machine learning to analyze data on brain function and brain wave patterns. Electrodes implanted in the subjects’ brains measured brain activity while the subjects attempted to memorize and recall information. The electrodes could also transmit electric shocks to the brain. Results showed that carefully timed shocks made people 13 percent more likely to recall material.

Flesch-Kincaid Grade Level of Article: 12.1

Extended Discussion Questions

• If this internal memory stimulation technology is adapted to an external stimulation device, what other groups of people might benefit most from it?
• Do you think this type of technology should be available to everyone? (Not just those with medical conditions that cause memory loss.) Why or why not?
• If this type of memory-enhancing technology became widely available to the public, who do you think would be able to take advantage of it first? Why?
  • If your test scores were being compared to someone who had an electronic memory stimulator, would you consider that fair? Would you want there to be rules against it?
  • Compare this technology with non-electronic test aids, like good study techniques, tutoring, or test prep classes. Who can use those aids? Do you think they’re fair?
• Are there any (other) potential drawbacks or dangers to this technology? (Example to start: Would you be concerned if there was data out there that showed when you were and weren’t paying attention?)
• Can you think of other examples where machine learning could help scientists identify patterns in brain activity? What would be the benefits of studying those patterns?

Global Impact Learning Objectives:

• LO 7.1.1 Explain how computing innovations affect communication, interaction, and cognition.
• LO 7.2.1 Explain how computing has impacted innovations in other fields.
• LO 7.4.1 Explain the connections between computing and real-world contexts, including economic, social, and cultural contexts.

Global Impact Essential Knowledge:

• EK 7.1.1L Computing contributes to many assistive technologies that enhance human capabilities.
• EK 7.2.1A Machine learning and data mining have enabled innovation in medicine, business, and science.
• EK 7.2.1G Advances in computing as an enabling technology have generated and increased the creativity in other fields.
• EK 7.3.1A Innovations enabled by computing raise legal and ethical concerns.

Other CSP Big Ideas:

• Idea 3 Data and Information
• Idea 4 Algorithms

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