An Ethics of Artificial Intelligence Curriculum for Middle School Students

Blakeley H. Payne, [email protected]

MIT Media Lab

Personal Robots Group directed by Cynthia Breazeal

August 2019

A student shows off her paper prototype for her redesign of YouTube.

Table of Contents

Table of Contents 1

Introduction 3

About 3

Usage 4

How to Access Materials 4

Translated Materials 5

Feedback 6

Learning Objectives 7

Activities 10

Overview 10

AI Bingo 13

Description 13

Slides 13

Instructions 13

Worksheet 14

Introduction to Algorithms As Opinions 16

Description 16

Slides: 16

Teacher Guide 17

PB&J Sandwich Activity Sheet 20

Ethical Matrix 22

Description 22

Slides 22

Teacher Guide 23

Ethical Matrix Activity Sheet 26

Introduction to Supervised Machine Learning and Algorithmic Bias 29

Description 29

Slides 29

Teacher Guide 30

Introduction to Supervised Machine Learning Activity 36

Image Datasets 38

Initial Training Dataset 40

Dogs 40

Cats 46

Test Dataset 56

Recurating Dataset 61

Dogs 61

Cats 65

Introduction to Algorithmic Bias Activity Sheet 69

Supervised Machine Learning Quiz 77

Speculative Fiction 80

Description 80

Slides 80

Instructions 80

Unplugged Modification 82

Speculative Futures Activity Version #1 83

Speculative Futures Activity Version #2 85

Speculative Futures Activity Version #3 87

Speculative Futures Activity Version #4 89

YouTube Scavenger Hunt 91

Description 91

Teacher Guide 93

YouTube Scavenger Hunt Activity Sheet 96

YouTube Redesign 97

Description 97

Slides 97

YouTube Redesign Activity Guide 98

YouTube Socratic Seminar 102

Description 102

Instructions 102

Reading 102

Socratic Seminar Questions 104

Acknowledgements 105

Introduction

A pair of students work on their paper prototype of YouTube after completing an ethical matrix.

About

This document includes a set of activities, teacher guides, assessments, materials, and more to assist educators in teaching about the ethics of artificial intelligence. These activities were developed at the MIT Media Lab to meet a growing need for children to understand artificial intelligence, its impact on society, and how they might shape the future of AI.

This curriculum was designed and tested for middle school students (approximately grades 5th-8th). Most activities are unplugged and only require the materials included in this document, although unplugged modifications are suggested for the activities which require computer access.

Usage

License: CC-BY-NC under Creative Commons

These materials are licensed as CC-BY-NC under creative commons. This license allows you to remix, tweak, and build upon these materials non-commercially as long as you include acknowledgement to the creators. Derivative works should include acknowledgement but do not have to be licensed as CC-BY-NC.

To acknowledge the creators, please include the text, “An Ethics of Artificial Intelligence Curriculum for Middle School Students was created by Blakeley H. Payne with support from the MIT Media Lab Personal Robots Group, directed by Cynthia Breazeal.”

More information about the license can be found at: https://creativecommons.org/licenses/by-nc/4.0/

People interested in using this work for for-profit commercial purposes should reach out to Cynthia Breazeal at [email protected] for information as to how to proceed.

How to Access Materials

In order to use and edit the materials below, please make a copy of this document by:

1. Making sure you are logged into your Google account.

2. Go to File > Make a copy

3. You will then be prompted to name and save the materials to your drive.

All slides can be found at: https://drive.google.com/open?id=1gp2Hywu8sOoweEc2NQb6V-yiXAuSolnC

Each slide deck is also linked below with its corresponding activity. In order to access slides, make sure to follow the steps above to add them to your Google Drive.

Translated Materials

We are very fortunate that these materials have been translated by many individuals all across the globe. You can access these translated materials here:

German: https://thingminds.ch/de/kikids/

Translated by Eugen Rodel of thingminds.

Portuguese (partial translation as well as remixed materials): https://drive.google.com/drive/folders/1NhCTVNm-qg5BaMAdiTjvG1Ulebh6OJqE

Translated by Miguel Angelo Abreu Sousa of the Federal Institute of Sao Paulo, Brazil.

Korean: https://keris.or.kr/main/ad/pblcte/selectPblcteETCInfo.do?mi=1142&pblcteSeq=13255

Translated by Dr. Han-Sung Kim of the Korea Education and Research Information Service.

Feedback

Thank you for checking out our AI + Ethics Curriculum! We plan to continuously evaluate and iterate on this work, so please consider filling out the following survey to give us your feedback (~5 min in length):

https://mit.co1.qualtrics.com/jfe/form/SV_6X5UWiD7p58BnNz

Additional feedback you may have to [email protected]. We’d love to hear which resources you use, with what age groups, and any feedback you’d like to give for future iterations of this curriculum!

Learning Objectives

1. Understand the basic mechanics of artificial intelligence systems.

1. Recognize algorithms in the world and be able to give examples of computer algorithms and algorithms in everyday contexts (for example, baking a cake).

2. Know three parts of an algorithm: input, steps to change input, output.

3. Know that artificial intelligence is a specific type of algorithm and has three specific parts: dataset, learning algorithm, and prediction.

1. Understand the problem of classification in the supervised machine learning context.

2. Understand how the quantity of training data affects the accuracy and robustness of a supervised machine learning model.

4. Recognize AI systems in everyday life and be able to reason about the prediction an AI system makes and the potential datasets the AI system uses.

2. Understand that all technical systems are socio-technical systems. Understand that socio-technical systems are not neutral sources of information and serve political agendas.

1. Understand the term “optimization” and recognize that humans decide the goals of the socio-technical systems they create.

2. Reason about the goals of socio-technical systems in everyday life and distinguish advertised goals from true goals (for example, the YouTube recommendation algorithm aims to make profit for the company, while it is advertised as a way to entertain users).

1. Map features in existing socio-technical systems to identified goals.

3. Know the term “algorithmic bias” in the classification context.

1. Understand the effect training data has on the accuracy of a machine learning system.

2. Recognize that humans have agency in curating training datasets.

3. Understand how the composition of training data affects `the outcome of a supervised machine learning system.

3. Recognize there are many stakeholders in a given socio-technical system and that the system can affect these stakeholders differentially.

1. Identify relevant stakeholders in an socio-technical system.

2. Justify why an individual stakeholder is concerned about the outcome of a socio-technical system.

3. Identify values an individual stakeholder has in an socio-technical system, e.g. explain what goals the system should hold in order to meet the needs of a user.

4. Construct an ethical matrix around a socio-technical system.

4. Apply both technical understanding of AI and knowledge of stakeholders in order to determine a just goal for a socio-technical system.

1. Analyze an ethical matrix and leverage analysis to consider new goals for a socio-technical system.

2. Identify dataset(s) needed to train an AI system to achieve said goal.

3. Design features that reflect the identified goal of the socio-technical system or reflect the stakeholder’s values.

5. Consider the impact of technology on the world.

1. Reason about secondary and tertiary effects of a technology’s existence and the circumstances the technology creates for various stakeholders.

Activities

Students work together to build their paper prototypes of YouTube.

Overview

The following table provides an overview of the activities included in the curriculum:

Name

Description

Standards

Time

AI Bingo

Students are given bingo cards with various AI systems. Students find a partner who has also used that AI system and together work to identify what prediction the system is making and the dataset it uses.

1.c, 1.d

30 min

Algorithms as Opinions

Students learn that algorithms, like recipes, are a set of instructions that modify an input to produce an output. Students are then asked to write an algorithm to make the ”best” peanut butter and jelly sandwich. Students then explore what it means to be ”best” and see how their opinions are reflected in their algorithms.

1.b

2.a, 2.c

45 min

Ethical Matrix

Building on the algorithms as opinions lesson, students identify the stakeholders who care about their peanut butter and jelly sandwich

algorithm and the values those stakeholders have in the algorithm. They then fill out an ethical matrix to see where those values overlap or conflict.

2.b

3.a, 3.b, 3.c, 3.d

4.a

45 min

Intro To Supervised Machine Learning & Algorithmic Bias*

Students are introduced to the concept of classification. By exploring Goog