Published By: CBS News/CNET, 4/1/2017
Researchers demonstrated that facial recognition software can diagnose a rare disease known as DiGeorge syndrome. The software can analyze photos taken by a smartphone, circumventing the need for gene analysis and allowing for early treatment. It is highly accurate across ethnic groups — whereas clinicians have more trouble diagnosing genetic diseases in non-Europeans. Similar software can diagnose Down’s syndrome, and the researchers are working on other genetic syndromes.
Flesch-Kincaid Grade Level of Article: 13.3
Extended Discussion Questions
- If a medical provider wanted to use facial recognition software to make a diagnosis for you, what questions or concerns might you have?
- Would you rather have a diagnosis from facial recognition technology or a specialist doctor? Why?
- How should medical providers use the software’s diagnosis when determining further testing/evaluation options?
- What types of clinics and patients will receive the most benefit from this technology? (Compared to what is possible now.)
- The article points out that it can be used by clinics that don’t have equipment for genetic testing. What do they need to be able to use this technology?
- (If you’ve talked about algorithmic and dataset bias) Think about some other examples of systems that use facial recognition software. What could the developers of those systems learn from the way this project was designed and implemented?
Relating This Story to the CSP Curriculum Framework
Global Impact Learning Objectives:
- LO 7.2.1 Explain how computing has impacted innovations in other fields.
- LO 7.3.1 Analyze the beneficial and harmful effects of computing.
- LO 7.4.1 Explain the connections between computing and real-world contexts, including economic, social, and cultural contexts.
Global Impact Essential Knowledge:
- EK 7.2.1A Machine learning and data mining have enabled innovation in medicine, business, and science.
- EK 7.2.1C Computing enables innovation by providing the ability to access and share information.
Other CSP Big Ideas:
- Idea 1 Creativity
- Idea 3 Data and Information
Banner Image: “Network Visualization – Violet – Offset Crop“, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0.