Chapter 5 – Artificial Intelligence (AI)

“The development of full artificial intelligence could spell the end of the human race.” – Stephen Hawking (BBC News, “Stephen Hawking warns artificial intelligence could end mankind“, 2014).

“[AI is] the biggest risk that we face as a civilization.” – Elon Musk, Tesla CEO (Wall Street Journal, “Elon Musk Lays Out Worst-Case Scenario for AI Threat“, 2017).

Overview

bride of frenkensteinIt seems inevitable that if computers can be programmed to “think” like humans, they would be employed to do the things humans do for humans. After all, wouldn’t it be nice if we all had our own personal assistant working 24/7 to answer questions and do tasks on our behalf?

In the past few years, a convergence of advanced technologies, development standards, and interconnectivity has made it possible for computers to recognize patterns in speech and data to interact in remarkably human-like ways. As you will see in this chapter’s articles, AI-generated text and images are becoming eerily human-like. Yet, there is very little regulation of AI throughout the world.

In this chapter, we will review the implications of artificial intelligence (AI) in the human environment.

Key Terms

Artificial Intelligence (AI) – “Artificial intelligence is the design, implementation, and use of programs, machines, and systems that exhibit human intelligence, with its most important activities being knowledge representation, reasoning, and learning.” (Whitson, G. P., 2013).

Artificial General Intelligence (AGI) – .”..[I]s when a computer program can perform any intellectual task that a human could.” (Astute Solutions). AGI, also referred to as “strong AI,” would have the ability to acquire new knowledge and skill on its own, learn from examples, and understand the context of a situation. Voss’ article (2017) provides a bullet list of eight points that describes the capabilities of an AGI algorithm. It is important to note that practical AGI machines do not yet exist.

Artificial Narrow Intelligence (ANI)  – “[R]efers to a computer’s ability to perform a single task extremely well, such as crawling a webpage or playing chess.” (Astute Solutions). Examples include computer vision (which is how Facebook is able to identify a person in a photo), Google Translate, and a commercial website offering you purchase suggestions based on your prior purchases. ANI is considered to be a “weak AI” because it can only do what it is designed to do and nothing more (Dickson, 2017), and its capabilities are limited to the programmer’s design. In other words, it cannot “self-learn” (Voss, 2017).

Artificial Super Intelligence (ASI)  – “[a]n AI [entity] that surpasses human intellect.” (Whitson, G. P., 2013). As with AGI, this level of AI does not yet exist as a practical technology.

Bot – A communication application designed to act as a virtual assistant using humanlike communication. Some use text alone, some use synthesized speech. Popular examples include: Alexa, Amazon Echo, Siri, Cortana, and Google Duplex. A Chat bot is a bot that interacts through a text based chat service.

Natural Language Processing: A machine learning method for interpreting language for the purpose of enabling computing systems to understand human communication. Read more at the Educause Learning Initiative’s (ELI) article “7 Things You Should Know About Natural Language Processing.”

Turing Test – .”..[A] test of a machine’s ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.” (Wikipedia). The roots of this expression are in the 1951 experiment conducted by Alan Turing to test human perception of machine intelligence. Since then, the expression “Does it pass the Turing Test?” has become a refrain for every demonstration of computer intelligence.

AI Subsets
AI is a classification that encompasses both Machine Learning and Deep Learning. (Image by Tukijaaliwa, CC BY-SA 4.0, via Wikimedia Commons)

Deep Learning – A method of producing a set of patterns by placing input data through multiple layers of computer processors. The goal is to process data in a way that mimics neural processing in the human brain to develop a “smarter” algorithms (Dickson, 2017). An example would include an algorithm that is able to detect cancer from scanning an X-ray – a process called “computer-aided detection.”  A definitive, in-depth description of Deep Learning’s capabilities and limitations is in Marcus’ (2018) article, “Deep Learning: A Critical Appraisal.”

Machine Learning – A process for programming a machine to learn from analysis of examples. For example, a computing device can be programmed to learn what a cat looks like by providing it with millions of pictures of cats so that patterns of similarity can be collected and then used as a basis for predicting the correct identity of a given sample (Dickson, 2018). The most recent application is found in the images generated on the This person does not exist website. There has been a historical problem with training data sets having metadata that reflects sexist, racist, and other biases, as shown in MIT’s retraction of a data set.

What should you be focusing on?

Your objectives in this module are:

  • Identify the different forms of AI.
  • Identify how various AI technologies are currently used in the real world.
  • Appraise the potential ways AGI/ASI might be useful.
  • Evaluate the benefits and risks of implementing AI.

Readings & Media

Thematic narrative in this chapter

In the following readings and media, the authors will present the following themes:

  1. AI has tremendous potential to assist people in everyday life.
  2. The use of AI poses extraordinary risks.
  3. AI is pretty cool!
  4. AI will kill us all. Or maybe not.

    Required     Examples of AI technologies (4:11)

Google Duplex bot: Here is a demonstration of Google Duplex, an ANI, being used to make phone calls to schedule tasks. If you go to the video’s listing in YouTube (by clicking on the YouTube icon on the lower right of the video player) be sure to check out the creative comments from people who are already imagining what else this kind of bot will be useful for.

    Experiment     ChatGPT: Create an account and try it out. (30:00)

ChatGPT is an artificial intelligence chatbot that can respond to questions in a dialog format. Technology pundits have universally described this version of chatbot as a stunning improvement over past attempts and have decried it as “the thing that shows what the future will be like.” The implications for undermining our education system has resonated across the industry. The Hackernoon blog has published an article that describes how ChatGPT works at five levels of difficulty. Familiarize yourself with the workings of ChatGPT according to the “Graduate Student” level.

As January, 2023, ChatGPT is still a freely accessible system. When you reach the dashboard, type in a question of your own according to the style posted in the Examples column. After the answer is produced, follow-up with additional questions or clarifications.

    Experiment     ThisPersonDoesNotExist: A realtime image generator of realistic-looking people. (15:00)

When you land at this website, it will show you a randomly generated portrait of a person that does not exist. Go to the lower right corner and click through some of the other image generators (art, cats horses, etc.) and click through the numbered links that explain how it works.

    Experiment     DALL•E 2: Create an account and try it out. (If you already created an account for ChatGPT, you can use the same login). (15:00)

As the website states, “DALL·E 2 is a new AI system that can create realistic images and art from a description in natural language.”

As January, 2023, DALL•E 2 is still a freely accessible system. When you reach the dashboard, type in a description of an image you want generated. Once you type in your text and click the black Generate button, it will take a few seconds to generate your images.

    Required     Article: The New York Times “We Need to Talk About How Good A.I. Is Getting” by Kevin Roose, August 24, 2022.

This article is a combination of expository on the most recent innovations using AI along with commentary about their implications. Read closely in the latter half of the article where the author proposes responses to risks and opportunities.

Roose, K. (2022). We Need to Talk About How Good A.I. Is Getting. The New York Times. https://www.nytimes.com/2022/08/24/technology/ai-technology-progress.html

    Required     Website: Explore the tenets of the Algorithmic Justice League. (15:00)

The Algorithmic Justice League is an organization leading the call for accountability in AI. Skim and explore the topics on the forefront of concern related to the use of algorithmically developed AI. Skim The Brookings Institute’s “Artificial intelligence and bias: Four key challenges” (2019) which describes the inherent flaws in the development of AI systems using flawed training data and human cultural projection.

    Required     Articles: Explore the range of AI applications in everyday use. 

AI’s invisible hand on daily life” (2022) (14 pages)

Definitive List of Artificial Intelligence Examples In Use” (2018). Scroll to the bottom to review the list. (5 pages)


Optional: Supplemental resources that are relevant to AI

The New York Times: If you have an interest in law enforcement, review “Can We Make Our Robots Less Biased Than We Are?” which describes the use of robots in police work as way to de-escalate conflict.

Military Applications of Artificial Intelligence – Ethical Concerns in an Uncertain World: This article from 2020 is only available in-full for a fee, but the Key Findings are offered for you to review. In another article, “How Well Can AI Pick Targets From Satellite Photos? Army Test Aims to Find Out,” the Army is evaluating ways to include AI in assessing targets.

The Guardian: “Weaponised AI is coming. Are algorithmic forever wars our future?” – Weaponized AI in military operations to determine who are suitable targets for killing.

The Chinese government has developed an AI “prosecutor” that evaluates evidence of criminal activity to determine whether someone should be arrested and prosecuted.

Synthesia: A comprehensive video development application that generates AI humans in promotional videos. A company called Generated Photos provides AI-generated photos of people to use for marketing and other creative purposes. Since these are images of people who do not exist, there are no legal clearances, royalties, or copyrights required.

AI Weirdness: Janelle Shane writes about .”..the intersection between art and science.” She has published the AI Weirdness blog that describes the results of .”..training neural networks to write unintentional humor as they struggle to imitate human datasets.” Check out the results of an AI bot producing the names of “high tech pies that sound really old” and some indescribable Halloween costume ideas. If you are truly courageous, check out the artificially generated photo images produced by the BigGAN system. Some are beautiful; some cannot be unseen.

The New Yorker:How Frightened Should We Be of A.I.?” by Tad Friend (May 14, 2018). This well-cited article introduces some speculative questions about the consequences of AGI development. There are many references to popular media that help explain the issues. The article’s style is very accessible for a non-technical audience.

Educause – 7 Things to Know…:  Natural Language Processing: “Natural language processing combines the power of artificial intelligence with linguistics to process and analyze language-based data.” From the Educause Learning Initiative.

Princeton research: Dialogues on AI and Ethics. This collection of fictional case studies is designed for use by educators to think about the ethical ramifications of AI in healthcare, sound identification, and education.

A collection of bot apps:  Chatbottle.co is an aggregator for bot applications you can use through your Facebook, Skype, Slack, Telegram, and Kik accounts. Click on some and play around in your Facebook or Skype account.

MIT Technology Review: AI-discovered molecules – Scientists have used AI to discover promising drug-like compounds.

Create you own bot: “Build a chatbot for your business in minutes!” on botwiz.ai.

For developer geeks:Anatomy of an AI System” shows a schematic model of how an AI system is developed. ImageNet is an image resource for use in training AI systems.

The Atlantic:Can Artificial Intelligence Predict Religious Violence?.” AI is used to quantify the conditions of religious conflict and predict when the conditions of a situation might lead to violence.


References

Dickson, B. (2017, May 12). What is Narrow, General and Super Artificial Intelligence. Retrieved June 9, 2018 from https://bdtechtalks.com/2017/05/12/what-is-narrow-general-and-super-artificial-intelligence/

Dickson, B. (2018, February 27). The limits and challenges of deep learning. Retrieved June 9, 2018 from https://bdtechtalks.com/2018/02/27/limits-challenges-deep-learning-gary-marcus/

Dickson, B. (2018, March 16). What is machine learning? Retrieved June 9, 2018 from https://bdtechtalks.com/2017/08/28/artificial-intelligence-machine-learning-deep-learning/

Marcus, G. (2018). Deep Learning: A Critical Appraisal. arXiv preprint arXiv:1801.00631. Retrieved June 9, 2018 from https://arxiv.org/abs/1801.00631

Voss, P. (2017, October 3). From Narrow to General AI and from External to Internal Intelligence. Retrieved June 9, 2018 from https://medium.com/intuitionmachine/from-narrow-to-general-ai-e21b568155b9

Whitson, G. P. (2013). Artificial intelligence. Salem Press Encyclopedia Of Science,

Photo Credit: Photo of Elsa Lanchester and Boris Karloff from the 1935 film The Bride of Frankenstein via Wikimedia Commons CC0.

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Chapter 5 - Artificial Intelligence (AI) by Steve Covello is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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