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[DSC Europe 23] Rania Wazir - Opening up the box: the complexity of human interaction with AI systems

AI systems are human-made: This fact is so obvious, that we often overlook it. From inception until disposal, an AI system is shaped by human decisions. Questions such as which types of AI research to fund, and how many resources to commit; which functionalities a particular AI system should have, and what the optimization function should be; where training data should come from, what is to be classified and how, and how to interpret system outputs – these are all decisions made by people. AI systems do not operate in a vacuum. Our inputs define the system, and the system outputs, in turn, influence their environment, affecting us and our world. This is the key, both to recognizing the risks of AI, and to understanding how to mitigate them.

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Opening up the box:
the complexity of human
interaction with AI systems
DSC Belgrade, 22.11.2023
Rania Wazir, Ph.D.
Co-founder & CTO, leiwand.ai
Dr. Gertraud Leimüller
Co-founder & CEO, leiwand.ai
Rania
Expert in ML, NLP, and
Trustworthy AI, with focus on
Algorithmic Fairness; leadership
roles in international AI Standards
Co-founder and CTO
Gertraud
Open-Innovation expert,
business and social science
lead in Trustworthy AI,
experienced in transforming
organisations;
Co-founder and CEO
Thomas
Social Science background,
open-source specialist, NLP
and ML expert
Data Scientist – Head of
MLOps
Bettina
Background in creative and
cultural industries; Trustworthy
AI in labor markets
Project Manager
Who we are
Silvia
Background in Political
Science and Communication;
Digital Transformation and
Open Innovation Expert
Chief Strategist
Mira
Linguistics background, NLP
and ML expert
Data Scientist
Patrick
Background in Philology;
writer, multimedia journalist
Communications Manager
leiwand.ai 2023
Where do AI
systems
come from?
Rania Wazir, PhD - leiwand.ai
“The impacts of AI are not
inevitable. They’re a result of
the choices that we make about
how we use these algorithms as
well as what algorithms to use”
-David Rolnick, assistant professor in computer science,
McGill University & Mila
Bigger is better?
Bigger is better?
The Race to Make AI Smaller, Smarter
"We challenge people to think small and focus
more on building efficient systems that can be
used by more people"
- Aaron Mueller, Johns Hopkins University
BabyLM Challenge: JHU & ETH Zurich
Combating Harmful Hype in Natural Language
Processing
“we outline the harms speakers of non dominant
languages have experienced due to these
grandiose and inaccurate claims, ranging from
diverting resources from local startups to low
quality datasets and models”
- Hadgu, Azunre, Gebru

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[DSC Europe 23] Rania Wazir - Opening up the box: the complexity of human interaction with AI systems

  • 1. Opening up the box: the complexity of human interaction with AI systems DSC Belgrade, 22.11.2023 Rania Wazir, Ph.D. Co-founder & CTO, leiwand.ai Dr. Gertraud Leimüller Co-founder & CEO, leiwand.ai
  • 2. Rania Expert in ML, NLP, and Trustworthy AI, with focus on Algorithmic Fairness; leadership roles in international AI Standards Co-founder and CTO Gertraud Open-Innovation expert, business and social science lead in Trustworthy AI, experienced in transforming organisations; Co-founder and CEO Thomas Social Science background, open-source specialist, NLP and ML expert Data Scientist – Head of MLOps Bettina Background in creative and cultural industries; Trustworthy AI in labor markets Project Manager Who we are Silvia Background in Political Science and Communication; Digital Transformation and Open Innovation Expert Chief Strategist Mira Linguistics background, NLP and ML expert Data Scientist Patrick Background in Philology; writer, multimedia journalist Communications Manager leiwand.ai 2023
  • 4. Rania Wazir, PhD - leiwand.ai “The impacts of AI are not inevitable. They’re a result of the choices that we make about how we use these algorithms as well as what algorithms to use” -David Rolnick, assistant professor in computer science, McGill University & Mila
  • 6. Bigger is better? The Race to Make AI Smaller, Smarter "We challenge people to think small and focus more on building efficient systems that can be used by more people" - Aaron Mueller, Johns Hopkins University BabyLM Challenge: JHU & ETH Zurich Combating Harmful Hype in Natural Language Processing “we outline the harms speakers of non dominant languages have experienced due to these grandiose and inaccurate claims, ranging from diverting resources from local startups to low quality datasets and models” - Hadgu, Azunre, Gebru
  • 7. Garbage in, garbage out ... 7 In New York, the lawyer for the plaintiff in a case against the Colombian Airline Avianca  used chatGPT to undertake background research for the case  the chatbot delivered 6 precedence cases  during the court proceedings, it was discovered that the 6 cases were complete fabrications Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 8. Garbage in, garbage out ... 8  Reuters, Amazon abandoned AI recruiting tool that favored men for technical jobs, The Guardian, 11.10.2018. Franzen, C., The AI feedback loop: Researchers warn of ‘model collapse’ as AI trains on AI-generated content, VentureBeat, 12.06.2023. Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 9. The value of input labor ... 9 Perrigo, B., Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic, Time Magazine, 18.01.2023.  AP: Seventeen authors have joined a new lawsuit alleging ‘systematic theft on a mass scale’ by the program, The Guardian, 20.09.2023. Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 10. What to optimize for ... 10 AI in medical diagnostics: SCIENCE Magazine: “Dissecting racial bias in an algorithm used to manage the health of populations.”  Algorithm used to predict the severity of patient illness, in order to decide on in- patient or out-patient care  Trained on historical patient data, optimized on amount of money spent to cure patient Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 11. How to evaluate system performance ... 11 Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 12. Decisions based on AI system output ... 12 NY Times, Wrongfully Accused by an Algorithm  A black man is arrested by Detroit Police, at home, in front of his wife and children  false identification through facial recognition software, and ineffective human oversight Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 13. “Algorithms are human creations, and subject to error like any other human endeavor.” US Judge Stephen Smith Rania Wazir, PhD; Dr. Gertraud Leimüller - leiwand.ai
  • 14. We can do better ... Overcoming human prejudices with the help of AI systems – to detect sources of pain that are often overlooked by radiologists: Pierson et al., An algorithmic approach to reducing unexplained pain disparities in underserved populations, January 2021. Rania Wazir, PhD - leiwand.ai
  • 15. 15 We can do better Reducing the footprint of recycled steel: Fero Labs uses AI to help steel manufacturers reduce the use of mined ingredients by up to 34%, preventing an estimated 450,000 tons of CO2 emissions per year Rania Wazir, PhD - leiwand.ai
  • 16. Thank you for listening! Stay in touch! Rania Wazir, PhD rania.wazir@leiwand.ai Dr. Gertraud Leimüller gertraud.Leimueller@leiwand.ai
  • 17. Rania Wazir, PhD - leiwand.ai Some further references Bender et al., On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?, FAccT ’21, 2021. Buolamwini, J. and Gebru, T., Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification, Proceedings of Machine Learning Research 81:1–15, 2018. Crawford, K., ”Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence”, Yale University Press, 2021. Dressel, J. and Farid, H., The accuracy, fairness, and limits of predicting recidivism, https://advances.sciencemag.org/content/4/1/eaao5580 Kucharavy, A., et al. Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense Narayanan, A., ChatGPT is a bullshit generator. But it can still be amazingly useful. https://aisnakeoil.substack.com/p/chatgpt-is-a-bullshit-generator-but Raji et al., The Fallacy of AI Functionality, FAccT ’22, 2022. Sap et al., The Risk of Racial Bias in Hate Speech Detection, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 1668 – 1678, 2019. Semuels, A., The Internet Is Enabling a New Kind of Poorly Paid Hell, in The Atlantic, January 23, 2018. https://www.theatlantic.com/business/archive/2018/01/amazon-mechanical-turk/551192/ Stackoverflow, Why posting GPT and ChatGPT generated answers is not currently acceptable: https://stackoverflow.com/help/gpt-policy Strubell et al., Energy and Policy Considerations for Deep Learning in NLP. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 3645–3650, 2019. van Wynsberghe, A., Sustainable AI: AI for sustainability and the sustainability of AI, AI Ethics 1, 213–218, 2021. Measuring the performance of an AI system: Wazir, R., AI comedy of errors, or: The importance of choosing your AI performance metric with care, Blog post, April 2022 Why Meta’s latest large language model survived only three days online https://www.technologyreview.com/2022/11/18/1063487/meta-large-language- model-ai-only-survived-three-days-gpt-3-science/ Front Cover photo by Joakim Honkasalo on unsplash: https://unsplash.com/de/fotos/ssvjJLB6wIw