Ethical Implications of Artificial Intelligence

As artificial intelligence (AI) continues to advance at an unprecedented rate, there is an urgent need to consider its ethical implications. AI has the potential to revolutionize many industries, but it also presents new challenges and risks. Programmers play a critical role in shaping the development and deployment of AI, and must therefore be aware of its ethical implications.

In this session, we will explore the ethical considerations of AI and its impact on society. We will examine the challenges of developing and deploying AI systems that are unbiased, transparent, and accountable. We will discuss the ethical implications of AI in different fields, including healthcare, finance, and transportation. We will also explore the role of programmers in ensuring that AI is developed and deployed ethically.

Finally, we will discuss best practices for ethical implementation of AI, including designing for transparency, fairness, and accountability. We will also consider the importance of ethical decision-making frameworks and guidelines for AI development and deployment. By the end of this session, participants will have a better understanding of the ethical implications of AI and how they can play a role in ensuring that AI is developed and deployed ethically.

1. Ethical Implications of Artificial Intelligence Jeff McWherter Chief Operating Officer @jmcw

2. Ethics The What Ethics examines the rational justification for our moral judgments; it studies what is morally right or wrong, just or unjust. In a broader sense, ethics reflects on human beings and their interaction with nature and with other humans, on freedom, on responsibility and on justice. https://www.canada.ca/en/treasury-board-secretariat/services/values-ethics/code/what-is-ethics.html

3. Ethics The Importance Ethics is what guides us to tell the truth, keep our promises, or help someone in need. There is a framework of ethics underlying our lives on a daily basis, helping us make decisions that create positive impacts and steering us away from unjust outcomes https://rahuleducation.org/our-scribes/ethics/

4. Isaac Asimov’s Laws of Robotics Law One – “A robot may not injure a human being or, through inaction, allow a human being to come to harm.” Law Two – “A robot must obey orders given to it by human beings except where such orders would conflict with the First Law.” Law Three – “A robot must protect its own existence, as long as such protection does not conflict with the First or Second Law.” Asimov later added the “Zeroth Law,” above all the others – “A robot may not harm humanity, or, by inaction, allow humanity to come to harm.” https://www.brookings.edu/articles/isaac-asimovs-laws-of-robotics-are-wrong/

5. \ https://www.historyofinformation.com/detail.php?id=3652 Artificial General Intelligence or AGI high-quality realistic judgment day image where AI's rule the world --ar 16:9 - Variations (Strong) by @jeff_mcwherter (fast)

6. The Alignment Problem robot picking a daisy in a green field --ar 16:9 - Image #4 @jeff_mcwherter

7. Types of AI Three different cute robots one is Dark Blue one is yellow one is red all looking at each other confused--ar 16:9 - Image #2 @jeff_mcwherter

8. Bias two developers working on a Drupal project looking at a computer --ar 16:9

9. Why Amazon’s Automated Hiring Tool Discriminated Against Women AI discriminating against woman --ar 16:9

10. ProPublica: Machine Bias Chat GPT Write a Python script to see if someone would be a good scientist

11. Transparency cute red robot opening his insides to show transparency --ar 16:9

12. Model Cards

13. Counter Factual Explanation C cute red robot opening his insides to show transparency --ar 16:9

14. Fairwashing unequal power --ar 16:9 - Image #2 @jeff_mcwherter

15. Digital Epidermalization how digital technologies, particularly biometrics, embed racial biases within their operations --ar 16:9

16. Systemic discrimination involves the procedures, routines and organizational culture of any organisation that, often without intent, contribute to less favourable outcomes for minority groups than for the majority of the population, from the organisation’s policies, programs, employment, and services. https://www.coe.int/en/web/interculturalcities/systemic-discrimination

17. What Can We Do To Fix Build it Better More Data More Diverse Data Police it Better Gender recognition AI, no matter how inclusive we try to make it, will always be premised because someone can look at you and tell you what your deal is, and that is always going to be incorrect.

18. Data Flatting Problem what is an image that relates to stealing cute red robot in an Art Heist: An artistic representation of a sophisticated art theft, showing thieves taking valuable paintings from a museum or gallery, possibly wearing black suits and masks, which adds an element of drama and intrigue. --ar 16:9

19. Create an image with Jason from Friday the 13th stunting cheerleaders using the style of Steve Jencks from Lansing Michigan and screamprints.com.

20. Workforce cute red robot in a Mechanical Turk machine --ar 16:9 - Image #4 @jeff_mcwherter

21. Distribution of Wealth cute red robot that looks like the monopoly man, with a top hat and monocle with gold coins in the background like scrooge mcducks money bin --ar 16:9 - Variations (Strong) by @jeff_mcwherter (fast)

22. Environmental Problem cute red robot holding a dead daisy that is drooping, with factories in the background with billowing smokestacks --ar 16:9 - Image #3 @jeff_mcwherter

23. What Can We Do To Fix Regulation - privacy laws, antitrust laws, copyright Data-Owning Democracy - you decide what to do Digital Socialism - owned by society Both Data-Owning Democracy and Digital Socialism recommend the redistribution of property to increase citizens' economic power because AI changes our concept of private property.

24. If we truly believe humans are equal, we need to do better.

25. The Alignment Problem Making variations for image #4 with prompt robot picking a daisy in a green field --ar 16:9 - Image #4 @jeff_mcwherter

26. cute red robot, creating another robot in a workshop --ar 16:9 - Image #2 @jeff_mcwherter Conclusions

27. When people talk about ethical AI, instead of talking Skynet; we should think about working conditions, climate change, and how to make the economy serve humans rather than the other way around. Abigail Thorn -Philosophy Tube

28. Thank you Jeff McWherter @jmcwherter [email protected]