Unit 6. Data VisualizationRevision Date: Jun 11, 2020 (Version 3.0)
The second session is a programming activity and requires using NetLogo (a tutorial is in the Unit 4 Lesson on Hypothesis Testing with NetLogo) or using Python with Bokeh (for more advanced students).
Students will be introduced to the topic of diversity and computational problems, learn about and discuss implications of the proliferation of algorithms in society, and reflect on how the quality of input data and small, sometimes unintended biases can lead to low quality solutions.
Student computer usage for this lesson is: required
Think-Pair-Share: Artificial intelligence algorithms in daily life?
Ask your students to list discuss what artificial intelligence algorithms they think affect them in daily life and how they are affected. How would it be different if those algorithms did not recognize them or treated them inappropriately? If an algorithm makes the wrong judgement about them, what would they do, who could they go to for help? It is OK if students are unsure about the answers as it leads into the following discussion.
Algorithms have become prominent and common in daily life. In particular, algorithms that use artificial intelligence (AI) or a technique called machine learning are employed to make decisions that affect us, sometimes in ways we aren't aware of and cannot control. For example, machine learning is used by Google, Facebook, Flickr, among other companies to detect faces in photographs, apply labels, or automatically tag images with people they recognize. In general, these algorithms are trained on input data (such as images of people), and are improved iteratively using statistical methods until they learn how to categorize, differentiate, and reach a correct answer. Another example of companies using AI is in personalized marketing or recommendation systems. For instance, Amazon tailors the products they suggest based on an algorithm trained on similar customers' purchase history. Or a company like Netflix will recommend movies to users who rate similar movies similarly.
At the heart of these algorithms is the fact that their solutions all depend on the initial parameters and input data used to train them. What happens when those parameters and data are not sufficiently diverse? Small changes in those parameters, oversights in the training data, implementer bias (both intended and not), and missing distributions or categories can all negatively prejudice algorithms. All this is important to keep in mind as algorithms start determining aspects of our lives and there is less or no control over the input and decisions they make about and for us. Computing innovations can reflect existing human biases because of biases written into the algorithms or biases in the data used by the innovation.
Effective collaboration produces computing innovations that reflect the diversity of talents and perspectives of those who design them. A 2016 article in the New York Times (http://www.nytimes.com/2016/06/26/opinion/sunday/artificial-intelligences-white-guy-problem.html?_r=0) highlights an example problem where lack of diversity among devlopers lead to a lower quality solution. When teams developing various AI and machine learning algorithms lacked diversity they failed to recognize errors from calibrating on too limited a population. This lead to significantly bad results, such as not recognizing people with dark skin tones or tagging them inappropriately. Examples where diversity may greatly influence the quality and real-world implications of algorithms include:
Parable of the Polygons
A hands-on example of how initial parameters, subtle biases, and lack of diversity can greatly affect an algorithm's execution is in the "Parable of the Polygons" (http://ncase.me/polygons/). The Parable of the Polygon is a simulation based on the mathematical model of how segregated communities may arise from small differences preferences, based on the theory of Thomas Schelling, an economist and game theorist who received the Nobel Prize for Economics in 2005.
Guide students through the website and let them explore dragging polygons, changing settings, and see how they can influence (it is best for them to follow along individually or in groups on their own computer).
An alternative version of the final sandbox with three polygon shapes is also available here: http://ncase.me/polygons-pentagons/play/automatic/automatic_sandbox_frame.html
Journal or Homework
Have your students continue to explore the Parable of the Polygons website and answer the following questions using the sandbox at the bottom of the website:
Think-Pair-Share: Algorithms, Diversity, and Solutions [5 min]
Two options: guided programming exploration with NetLogo, or more involved Python programming project for advanced students
Option 1: Using NetLogo
Option 2: Using Python with Bokeh (for advanced students)
Journal: Have your students reflect and list 5 examples or ways in which diverse input makes for better solutions.
Questions in the AP Classroom Question Bank may be used for summative purposes.
Sixty of the 80 questions are restricted to teacher access. The remaining 20 questions are from public resources.
Questions are identified by their initial phrases.
A city government is attempting to reduce the d...
Discuss with the school’s AP Testing Coordinator before presenting to students.
Guidance for students in how to take the exam.
Confirm that students have access to the digital portfolio.
Think-pair-share: What is the digital portfolio for?
Share the AP Exam Administration presentation with students.