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01 / 05
Lesson Plan: Alan Turing

Blog Post | Computing

Lesson Plan: Alan Turing

In this lesson, students will learn about the tragic life of mathematical genius and key founder of theoretical computer science and artificial intelligence, Alan Turing.

Sean Kinnard —

You can find a PDF of this lesson plan here.

Lesson Overview

Featured article: Heroes of Progress, Pt. 34: Alan Turing by Alexander C.R. Hammond

In this lesson, students will learn about the tragic life of mathematical genius and key founder of theoretical computer science and artificial intelligence, Alan Turing.

Not only is Turing known as the ‘Father of Computer Science’ for his triumphs in both theoretical and applied computing, but his code-breaking work during World War II likely shortened the conflict and saved the lives of millions.

Warm-up

Watch this short video about the enigma code.

In partners, small groups, or as a whole class, have students respond to the following questions:

  • What was the enigma machine and why did the Germans think that its code wasunbreakable?
  • Why did the Poles believe that it was important to decode the enigma machine duringthe late 1930s?
  • How were the discoveries of Polish codebreakers transferred to the British and Frenchintelligence services?

Alan Turing and the team at Bletchley Park were able to break the German enigma code after a stroke of insight. Watch this clip from the award-winning 2014 biopic “The Imitation Game” for a dramatic (and historically-condensed) rendition of their important discovery. Then discuss the following questions:

  • Hitler’s cult of personality and Nazi dogma allowed Turing and his team to break the enigma code. Which habit of enigma operators was Turing and his team able to exploit? Specifically, what were the exact words the Nazis normally included in messages?
  • In the clip, Turing is shown using a large machine. Make a prediction. How was the invention of this machine able to help break German codes and shorten the war?

Questions for reading, writing, and discussion

Read the article, and then answer the following questions:

  • What has been the long-term significance of Turing’s 1936 academic paper “On Computable Numbers, with an Application to the Entscheidungsproblem” (i.e., decision problem)? How do the ideas in this document continue to affect our everyday lives?
  • What was the name of the machine that Turing invented that significantly helped in decoding the Nazi enigma code? What did this device do?
  • Turing’s brilliance was shown when he personally broke the code used by the German submarine fleet in 1941. Think about the larger context of World War II. Why was the breaking of that code of particular importance to Great Britain at that time? (The answer is not in the article; you must use your historical background knowledge.)
  • In the chart below, write a summary of Turing’s achievements in each field. In the right column, describe what you believe have been the most important impacts of each achievement.
What were Turing’s seminal achievements in this field?What were the most important impacts of that achievement?
Theoretical computing

Enigma code breaking

Hands-on creation of computers

Despite his heroic service to the Allied cause during World War II and his pioneering work on the world’s first computers during the late 1940s, Turing was publicly vilified in 1952 for engaging in homosexual activity and was cruelly punished by the British justice system. Tragically, Turing committed suicide in 1954 at the age of 41.

  • In subsequent years, how have Turing’s achievements been recognized? In what ways has the government of the United Kingdom tried to make amends for the savage injustice meted out to Turing?

Extension Activity/Homework

Make a Forecast

Almost 100 years ago, Alan Turing came up with the theoretical framework for modern computers. His academic work was the foundation for the laptops and smartphones that we now rely on every day.

Watch this short video on how Turing “accidently” invented the computer, and then respond to the following prompt:

How will computers evolve over the next 100 years? In a short essay, make a forecast about the types of tasks you think computers will be able to accomplish over the next century. Then describe how these advances will affect your everyday life. Write in detail about at least three changes you believe will occur as well as the specific ways people’s everyday experiences will change as a result.

Reflect on Your Own Reaction

How did reading about Turing’s life story affect you?

In a short reflective piece—either a paragraph, poem, song, drawing, or other creative medium of your choice—describe your personal reaction to Turing’s life story. Here are some ideas to get you started:

  • What is one word to capture your feeling after reading the article? How does that word capture your emotions?
  • What is one question you still have about Turing’s life and legacy?
  • What is one quote or detail from the article that particularly resonated with you? Why?

Science | Computing

DNA “Printing Press” Could Quickly Store Mountains of Data

“The invention of the printing press and movable type—metal letters that can be arranged and inked—led to the Renaissance and an explosion of information that continues to this day. Now, researchers report applying the concept of movable type at the molecular level to dramatically speed up the ability to encode data in strands of DNA, an incredibly high-density medium for storing information. Although only demonstrated in the lab so far, the new approach, reported today in Nature, could energize the emerging DNA data storage industry by making it cost effective to archive vital information for decades and beyond, independent researchers say.”

From Science.

Ars Technica | Computing

Anthropic Releases AI Tool That Can Take over the User’s Cursor

“AI software company Anthropic has announced a new tool that can take control of the user’s mouse cursor and perform basic tasks on their computer.

Announced alongside other improvements to Anthropic’s Claude and Haiku models, the tool is straightforwardly called ‘Computer Use.’ It’s available exclusively with the company’s mid-range 3.5 Sonnet model right now, via the API. Users can give multi-step instructions (Anthropic claims it can go for tens or even hundreds of steps) to accomplish tasks on the user’s computer by ‘looking at a screen, moving a cursor, clicking buttons, and typing text.’

…

Competing companies like OpenAI have been working on equivalent tools but have not made them publicly available yet. It’s something of an arms race, as these tools are projected to generate a lot of revenue in a few years if they progress as expected.

There’s a belief that these tools could eventually automate many menial tasks in office jobs. It could also be a useful tool for developers in that it could ‘automate repetitive tasks’ and streamline laborious QA and optimization work.”

From Ars Technica.

Live Science | Computing

New Quantum Computer Chip Now Outperforms Fastest Supercomputers in Certain Areas

“Quantum computers can outpace our fastest classical computers in very specific areas, a groundbreaking experiment suggests.

Google Quantum AI researchers have discovered a ‘stable computationally complex phase’ that can be achieved with existing quantum processing units (QPUs), also known as quantum processors.

This means that when quantum computers enter this specific ‘weak noise phase,’ they can perform computationally complex calculations that outpace the performance of the fastest supercomputers. The research — which was led by Alexis Morvan, a quantum computing researcher at Google — was published Oct. 9 in the journal Nature…

However, the data produced by quantum computers is still noisy, meaning they still need to do fairly intensive quantum ‘error correction’ as the number of qubits rises in order for the qubits to remain in the ‘weak noise phase,’ they added.”

From Live Science.

New York Times | Computing

Is Math the Path to Chatbots That Don’t Make Stuff Up?

“Chatbots like ChatGPT from OpenAI and Gemini from Google can answer questions, write poetry, summarize news articles and generate images. But they also make mistakes that defy common sense. Sometimes, they make stuff up — a phenomenon called hallucination.

Mr. Achim, the chief executive and co-founder of a Silicon Valley start-up called Harmonic, is part of growing effort to build a new kind of A.I. that never hallucinates. Today, this technology is focused on mathematics. But many leading researchers believe they can extend the same techniques into computer programming and other areas.

Because math is a rigid discipline with formal ways of proving whether an answer is right or wrong, companies like Harmonic can build A.I. technologies that check their own answers and learn to produce reliable information.”

From New York Times.