Will We Have Self-Driving Cars by 2030?

What the Machine Has to Learn

Free write (5 min): a rideshare arrives and there's no driver in it. Do you get in? The concrete version of the question gets far better writing than "how do you feel about autonomous vehicles."

Data work. The deck's opening half is history and mechanism:

• The 1956 GM Motorama film — "Key to the Future," predicting self-driving cars by 1976. Ask what it got right and what it got wrong. The deck intends it as a window into 1950s technology and 1950s culture, and students usually find it funny.
• The timeline, 1956–2019 — cable-guided cars in the 1960s, the DARPA challenges, Google starting quietly in 2009, Nevada licensing the first self-driven car in 2012, the first fatality in 2016, the first pedestrian fatality in 2018. Then ask for their own prediction.
• The levels of automation — have students identify the level of the cars they actually ride in, and find the level at which a driver is no longer needed.
• The machine-learning slides. Machine learning suits "simple and repetitive tasks at large scale." Then the list of what human drivers do without thinking: read the scene, infer why another driver is doing something, handle the exception (red light, but a police officer waving you through), and communicate with a pedestrian. Very little of that is simple or repetitive.
• The Turing test — could there be one for driving, and what would it look like? Turing's biography is a worthwhile short detour; he was persecuted for being gay, and the deck flags this deliberately.

Assign the readings — one from each group, with a quote pulled from each for Tuesday:

• Group A — 5 Big Challenges That Self-Driving Cars Still Have to Overcome (Vox) or No, You Won't Get Self-Driving Cars Anytime Soon (Verdict)
• Group B — Where the Billions Spent on Autonomous Vehicles by US and Chinese Giants Is Heading (CNBC) or How Driverless Cars Will Change Our World (BBC Future)

Quotes, Then the Questions Engineering Can't Answer

Mindful moment (5 min): Monday was the case for autonomy. What are the drawbacks and worries?

Breakouts (10 min): each student says which article they read, shares their quote, and explains why it stood out. Short, structured, and it gets every voice in the room before the formal seminar.

Then the four hard slides, in this order — they escalate:

• How safe is safe enough? The deck asks it brutally: how many American deaths per day would you accept in exchange for the benefits — 1, 10, 50, 100? Then the comparison: more than 100 Americans already die on the roads every day, about 90% of crashes are caused by human error, and nearly 60% of drivers in fatal crashes are intoxicated.
• The fatality-rate graph. Which line actually measures whether cars have gotten safer? (See the facilitation notes — this one has a right answer.)
• The ethical scenario. A mother with a stroller steps out; the car can swerve onto a sidewalk where two adults are talking, or stay its course. What's the ethical choice — and will we accept a computer making it?
• The liability scenario. A truck crosses the centre line and kills a self-driving car's passenger, in circumstances where no human driver could have avoided it. Who does the family sue?

Then the data problem: today's partly-automated cars generate about 25 gigabytes per hour, and a full sensor suite would produce roughly 43 gigabits per second. Set that against the storage-capacity chart, which has a logarithmic y-axis and a curve that has been flattening since the 1990s.

Open the Discussion

Mindful moment (5 min), then breakouts using the point-and-question each student prepared Tuesday. The core questions:

• How do you feel about self-driving cars — would you use one, or would you rather drive?
• Will we have them by 2030?
• Will there come a day when cars requiring drivers no longer exist?
• How much should we worry about hackers? A European cybersecurity agency report found autonomous vehicles vulnerable precisely because of the computing power inside them.

Before students leave: themes and lingering questions in the notebook, and each student posts one resource to the sharing board so classmates can read them before Thursday.

Student-Sourced Evidence

Mindful moment (5 min) — this one is personal: what have you driven, how old do you have to be for a permit where you live, and are you excited or frightened to learn?

Then students share resources, and each picks one classmate's link to read carefully and evaluate: why this one, and what does it add to what the week already covered? The deck's closing question is the one to end on — will machines ever be as good as us at some things, or will they eventually be better at everything?

Score Your Participation

The four reflective questions, then the participation matrix. Students also use the participation rubric to score the week and explain the score.