Published By: Network World, 2/7/2017
Toyota is investing 50 million dollars and partnering with Stanford University and the Massachusetts Institute of Technology (MIT) to develop artificial intelligence and robotics technology needed for advanced driver-assistance systems. While Toyota is not trying to develop a fully automated car, they note that incremental advances in such driver-aid systems could eventually lead to driverless smart cars.
Flesch-Kincaid Grade Level of Article: 13.8
Extended Discussion Questions
- Toyota assumes that a human will still be behind the wheel, and says the goal of the research is to develop systems that assist those humans.
- How can a driver-aid system detect and automatically react to situations to improve the driving experience, without taking control from the driver? (Prompt: What about anti-lock braking systems? Who’s in control?)
- How might a poorly designed driver-aid system impact a driver’s ability to control a vehicle?
- The article mentions that Toyota intends to research “future mobility” to help senior citizens get around. What other groups of people might benefit from driver-assistance systems?
- For example, from cars being able to collect and interpret sensory data?
- One of the research groups will be looking at the interactions between the AI systems and the human drivers.
- Do you think smart driver-aid systems should be able to decide whether and how to obey a given command? (Either verbal or by using physical controllers.) Why or why not?
- How do you think a driver might react if their car seemed to be ignoring a command? (Prompt: Again, think about anti-lock brakes.)
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.
Global Impact Essential Knowledge:
- EK 7.1.1L Computing contributes to many assistive technologies that enhance human capabilities.
Other CSP Big Ideas:
- Idea 4 Algorithms
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.