Pros and cons of AI use

Jeremiah Wilson
University of Michigan Dearborn
Comp 106
Professor Ian Kennedy
3/8/2026

Artificial Intelligence has gone from being a tool to being something that is a part of everyday life. From search engines and facial recognition systems to generative tools, AI is changing how people work, learn, communicate, and make decisions. While AI promises efficiency and innovation, they also raise very important questions regarding society. Concerns about surveillance, bias in algorithms, misinformation, and the future of human workers demonstrate that AI is not just a technological issue, it is a societal one that affects our lives daily both negatively and positively.

 My course examines how Artificial Intelligence has grown and how it is disrupting modern society as well as its benefits on modern society. One reason AI has gained so much popularity is because of the benefits it provides to modern society. AI systems can analyze massive amounts of data way faster than humans can and it can do things like summarizing an entire book that you just copy pasted into it giving you a good enough idea of what happened in the book to where you could pass a test or write an essay on it. Artificial Intelligence speed  and reliability has allowed researchers and organizations to identify patterns and solve complex problems. For example, AI is being used in medicine to help doctors become aware of diseases earlier and develop new treatments for them. According to Melanie Mitchell in Artificial Intelligence: A Guide for Thinking Humans, AI technologies are valuable because they can process enormous datasets and uncover patterns that humans might overlook. This ability makes AI an important tool for scientific discovery and technological innovation.

AI also solves everyday issues making it desirable to use AI. Using ai is like taking the elevator instead of walking up the stairs. Many people interact with AI technologies daily without realizing it. Navigation systems suggest the fastest routes, streaming platforms recommend movies or music, and online services use algorithms to personalize information for users. Researchers such as Stuart Russell and Peter Norvig state that AI already plays a major role in transportation systems, online services, and digital assistants that help people organize their lives. These technologies save time and allow individuals and organizations to focus on more complex or creative work.

Even though AI may have some benefits, artificial intelligence also raises serious ethical and social concerns. Many scholars argue that AI systems can reinforce inequality when they are trained on biased data or designed without considering broader social consequences. In Algorithms of Oppression, Safiya Umoja Noble argues that algorithms often reflect the biases of the societies that create them. As a result, AI systems used in areas such as hiring or policing can cause discrimination or unfair outcomes. Another way artificial intelligence could be harmful to people is providing an easy way out for things when sometimes it is not necessary. For example students that are meant to be learning are just having AI do the work for them or instead of getting up and turning the light off you tell Alexa to turn your light off, AI can make people lazy and overall affect their work ethic and willingness to learn. These issues show that AI is not simply a neutral technology but one that must be carefully studied and controlled.

The vast spread of AI usage around the world makes it necessary to examine not just their benefits but their risks as well. This course provides an explanation to how artificial intelligence has developed, how it functions in modern society sometimes without us knowing, and what ethical challenges it presents. By studying AI from technological, and social perspectives, students will be able to understand how these systems influence everyday life. Overall, the goal of this syllabus is to encourage readers to think about how AI can both benefit and harm their lives.

Primary Sources

• Turing, Alan. “Computing Machinery and Intelligence.” Mind, 1950. https://phil415.pbworks.com/f/TuringComputing.pdf

Secondary Sources

• Mitchell, Melanie. Artificial Intelligence: A Guide for Thinking Humans.https://en.wikipedia.org/wiki/Artificial_Intelligence:_A_Guide_for_Thinking_Humans
• Russell, Stuart, and Peter Norvig. Artificial Intelligence: A Modern Approach.https://people.engr.tamu.edu/guni/csce625/slides/AI.pdf
• Kaplan, Andreas, and Michael Haenlein. “Siri, Siri, in My Hand: Who’s the Fairest in the Land?” https://www.researchgate.net/publication/328761767_Siri_Siri_in_my_hand_Who's_the_fairest_in_the_land_On_the_interpretations_illustrations_and_implications_of_artificial_intelligence

This week introduces the basic definition of AI and how researchers understand it

Week 2: The History of AI Development

• Dartmouth Summer Research Project on Artificial Intelligence Proposal (1956). https://parhamdata.com/Dartmouth_1955_Proposal_for_AI_Research.pdf

Secondary sources

• Nilsson, Nils. The Quest for Artificial Intelligence. https://ai.stanford.edu/~nilsson/QAI/qai.pdf
• McCorduck, Pamela. Machines Who Think Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence
• Russell, Stuart. Human Compatible. https://maxkasy.github.io/home/files/other/ML_Econ_Oxford/human_compatible.pdf

Students explore how AI evolved from early research projects into what it is today

Primary Sources

• Demonstrations of recommendation algorithms and digital assistants.

Secondary Sources

• Zuboff, Shoshana. The Age of Surveillance Capitalism. url
• Brynjolfsson, Erik, and Andrew McAfee. The Second Machine Age. https://www.milkenreview.org/articles/book-excerpt-the-second-machine-age
• Davenport, Thomas, and Rajeev Ronanki. “Artificial Intelligence for the Real World.” https://www.the-digital-insurer.com/library/artificial-intelligence-for-the-real-world-by-thomas-h-davenport-and-rajeev-ronanki-deloitte/

This week focuses on how AI influences regular daily activities like navigation, shopping, and entertainment and even things in the medical field.

Primary Sources

• Case studies of AI in healthcare and scientific research.

Secondary Sources

• Topol, Eric. Deep Medicine. https://drerictopol.com/portfolio/deep-medicine/
• Mitchell, Melanie. Artificial Intelligence: A Guide for Thinking Humans.https://commonwealthteaching.psu.edu/ai/artificial-intelligence-a-guide-for-thinking-humans/
• Brynjolfsson, Erik, and Andrew McAfee. Machine, Platform, Crowd. https://www.scribd.com/document/446409868/Machine-Platform-Crowd-Andrew-Mc-pdf

Students examine how AI improves efficiency, scientific discovery, and healthcare innovation.

Primary Sources

 Examples of AI-generated art, music, and writing

Secondary Sources

 Hertzmann, Aaron. “Can Computers Create Art?” https://www.mdpi.com/2076-0752/7/2/18 

Elgammal, Ahmed. “AI and Art: Machine Creativity.” https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.raco.cat/index.php/Artno des/article/download/374040/467557/&ved=2ahUKEwi-oP3yn6OTAxW94ckDHbM_IXgQFnoECB4QAQ&usg=AOvVaw01MaX-2-5K0oVdeKHRZ9af 

Marcus, Gary, and Ernest Davis. Rebooting AI: Building Artificial Intelligence We Can Trust. https://virtualmmx.ddns.net/gbooks/RebootingAIBuildingArtificialIntelligenceWeCanTrust.pdf 

Students talk about how AI challenges traditional ideas about creativity and authorship.  

Primary Sources

• Government surveillance policy documents and facial recognition demonstrations.

Secondary Sources

• Lyon, David. Surveillance Society.https://archive.org/details/surveillancesoci0000lyon/page/n9/mode/2up
• Zuboff, Shoshana. The Age of Surveillance Capitalism. https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://we.riseup.net/assets/533560/Zuboff%252C%2BShoshana.The%2BAge%2Bof%2BSurveillance%2BCapitalism.2019.pdf&ved=2ahUKEwjenvvzmqOTAxWy6BoGHcfdKIgQFnoFCJIBEAE&usg=AOvVaw0VrIZOB7HFyUoIE71OlIt3
• Andrejevic, Mark. “Automated Media.” https://www.researchgate.net/publication/336060582_Automated_Media

Students learn how AI is used to monitor populations and collect personal information.

Primary Sources

• World Economic Forum report on automation and employment. https://www.weforum.org/publications/the-future-of-jobs-report-2025/in-full/

Secondary Sources

• Frey, Carl Benedikt, and Michael Osborne. “The Future of Employment.” https://futureoflife.org/data/PDF/michael_osborne.pdf
• Susskind, Richard, and Daniel Susskind. The Future of the Professions. https://medium.com/workandlife/the-future-of-professions-5cd1eb8f6b4e
• Brynjolfsson, Erik, and Andrew McAfee. The Second Machine Age.https://frankdiana.net/2014/01/31/the-second-machine-age-and-business-evolution/

This week examines how ai may transform jobs and different economic structures.

Primary Sources

Machine Bias by Julia Angwin examining racial bias in the COMPAS criminal justice algorithm.

Secondary Sources

• Noble, Safiya Umoja. Algorithms of Oppression. https://safiyaunoble.com/wp-content/uploads/2020/09/Algorithms_Oppression_Introduction_Intro.pdf
• Benjamin, Ruha. Race After Technology.https://listen.datasociety.net/episodes/race-after-technology

O’Neil, Cathy. Weapons of Math Destruction. https://ia800603.us.archive.org/12/items/fflch-livro-weapons-of-math-destruction-cathy-240826-220339/(FFLCH)%20LIVRO%20Weapons%20of%20Math%20Destruction%20-%20Cathy%20_240826_220339.pdf

This week shows how biased data and algorithms can reinforce discrimination.

Primary Sources

• UNESCO Recommendation on the Ethics of Artificial Intelligence.

Secondary Sources

• Floridi, Luciano et al. “AI4People—An Ethical Framework for AI.” https://ai4people.org/PDF/AI4People_Ethical_Framework_For_A_Good_AI_Society.pdf
• Mittelstadt, Brent et al. “The Ethics of Algorithms.” https://www.courts.wa.gov/subsite/mjc/docs/2019/The%20Ethics%20of%20Algorithms.pdf
• Binns, Reuben. “Fairness in Machine Learning.” https://proceedings.mlr.press/v81/binns18a.html

Students study ethical frameworks and policies for governing AI systems.

Primary Sources

• Public talks and interviews with AI researchers.

Secondary Sources

• Bostrom, Nick. Superintelligence.https://nickbostrom.com/superintelligence
• Tegmark, Max. Life 3.0. https://www.cag.edu.tr/uploads/site/lecturer-files/max-tegmark-life-30-being-human-in-the-age-of-artificial-intelligence-alfred-a-knopf-2017-aTvn.pdf
• Russell, Stuart. Human Compatible.https://maxkasy.github.io/home/files/other/ML_Econ_Oxford/human_compatible.pdf

The final week shows a few of the possible futures of AI and how societies might manage its development responsibly.

Assignments

Assignment 1 AI analysis. Students will select a real life Artificial Intelligence system and study its effects on society. The assignment should describe how the system works, the benefits it provides, and how it could be harmful instead of being a benefit.Requirements are 700 words minimum and  to use at least two secondary sources from the syllabus to support your analysis including specific examples or data demonstrating the system’s impact, Discuss both positive and negative effects on society.

Goal:
This assignment should encourage students to examine how AI technologies influence everyday life and ethical challenges they present.

Assignment 2 AI timeline 

Make a timeline of how ai has evolved throughout history. Timeline should also include at least 4 secondary sources.

Goal: to understand how ai has grown throughout history and notice patterns that could lead you to make predictions about what it will be in the future.

Reflective Letter

Designing this course on Artificial Intelligence and society, I organized the weeks to follow a progression that I felt would be the easiest for students to really understand and learn from. Starting with Week 1, I introduce students to the definition of AI and key historical figures like Alan Turing, providing essential background knowledge. Week 2 then explores the history of AI development, showing how early research led to the modern systems students encounter today. This sequential structure continues as the course examines AI in everyday life (Week 3), its benefits to society (Week 4), and emerging applications such as generative AI and creativity (Week 5). By structuring the course this way, students first gain context, then explore practical applications, and finally critically analyze societal impacts, concluding with Weeks 9 and 10 with ethics, regulation, and future considerations. This progression reflects my use of logos, ensuring the course builds knowledge and is made in a way that students can learn from  while connecting technological developments to societal consequences.

I believe my selection of sources demonstrates ethos really well, reflecting careful consideration of authority, relevance, and perspective. For example, in Week 5, the primary sources include examples of AI-generated art, music, and writing, while the secondary sources, such as Aaron Hertzmann’s “Can Computers Create Art?” and Ahmed Elgammal’s “AI and Art: Machine Creativity”,which  provides a good scholarly analysis of generative AI. In Week 8, the primary source “Machine Bias” by Julia Angwin illustrates algorithmic bias in the criminal justice system;my secondary sources also support this. This combination emphasizes evidence of biased AI systems and the scholarly examination of their societal implications, reinforcing credibility and relevance in the curriculum.

In conclusion, the course design and sources work together to help students learn in a way where it makes sense. The weeks build logically from history to current situations and societal concerns. This approach ensures students develop a clear understanding of how AI affects modern life, and also how to critically analyze the ethical and social issues stemming from AI.