Ai in Society
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This document discusses artificial intelligence (AI) in society and key issues around its development and use. It begins with an introduction to AI applications in areas like personalized recommendations, customer service, and fraud detection. It then covers a 5-spoke framework for understanding AI systems, including components like perception, reasoning, communication, decision-making, and interaction. Examples of applications in areas like computer vision, natural language processing, and reinforcement learning are provided. The document also discusses issues like bias, fairness, ethics, accountability and transparency in AI. It profiles Singapore as a thought leader in developing frameworks for ethical and responsible AI.
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Ai in Society
- 1. Artificial Intelligence & Society Fireside Chat LUIS F. GONZALEZ https://www.linkedin.com/in/lgeai/
- 2. Confused Yet? It’s ok, we all are
- 3. Agenda Intro to AI in Society (Learning Algorithms) 20 mins Understanding AI (5 Spokes Framework) 30 mins • How they help & What it can go wrong • FEAT (Fairness, Ethics, Accountability & Transparency Singapore as thought leader 10 mins • Future of Applied AI
- 5. 5 Learn user’s behaviour based on voice commands and can adjust settings automatically in subsequent interactions Target user with personalized products and services ads based on their demographic profile, search history, visited sites, liked social media posts, etc. Improve efficiency/quality in servicing customers by using AI assistants (e.g., chatbots, robo-greeters in bank branches and cardless ATM machines via facial recognition) Detect suspicious/fraudulent activities in network and/or transactions using predictive analytics Recommend music or videos based on user’s historical consumption and preferences Provide best driving routes, ETA, and/or match drivers with riders based on historical and real- time data Smart Home Devices Media & Entertainment Navigation and Transportation E-commerce & Targeted Ads Customer Service Assistants Security and Fraud Detection What we see every day….
- 7. Capitalising on deadly sins and fears in the name of profit Exploiting the Human Condition
- 8. But with the potential to Improve the Human Experience https://aixexchange.com/#levels-of-aix-framework
- 9. 5 SPOKES AI FRAMEWORK homo-cognitio
- 10. What are the Components of AI? Sensing the world Perception Learning from every interaction Communication Optimizing to specific outcomes Decision making Understanding concepts & relations Reasoning Taking actions in the world to achieve goals Interaction Computer Vision Natural Language Understanding & Generation Forecasting and Operations Research Knowledge Graphs and Representations Reinforcement Learning Answer questions about a scene Determine if a growth is cancerous or not Infer what happened to characters in a story Drive on city streets and highways Identify objects in a scene
- 11. Perception: Vision and its applications https://aidemos.microsoft.com/computer-vision Try it your self
- 13. Reasoning : Use case Covid 19 treatment Knowledge Graphs Leading Practice
- 14. Communication: Natural Language U/G/P https://corenlp.run/ Try it your self
- 15. Other Applications today For NLP/G/U Abstract Summarization helps us understand your Context:
- 16. https://towardsdatascience.com/deep-learning-for-time-series-classification-inceptiontime-245703f422db letting the model learn how to process time series data on its own is a more promising solution when dealing with unstructured noisy data. Autoregressive CNN for Asynchronous Time Series Decision: Time Series and its applications https://youtu.be/U9yZIaVMa2c Try it your self
- 17. Interaction: Reinforcement Learning Reward Functions https://youtu.be/n2gE7n11h1Y Try it your self
- 18. Reinforcement Learning: Dynamic Treatment Regimes Interaction: Reinforcement Learning and its Applications
- 19. Ethical AI
- 20. Sensing the world Perception Learning from every interaction Communication Optimizing to specific outcomes Decision making Understanding concepts & relations Reasoning Taking actions in the world to achieve goals Interaction Computer Vision Natural Language Understanding & Generation Forecasting and Operations Research Knowledge Graphs and Representations Reinforcement Learning Answer questions about a scene Determine if a growth is cancerous or not Infer what happened to characters in a story Drive on city streets and highways Identify objects in a scene Mis-identification of Threat Dis-advantaging Groups Promoting Hate Speech Incrementing Market Volatility Pedestrian Fatality -Autonomous Vehicles What are the implications to humans?
- 21. Fairness Ethics Accountability Transparency FEAT principles were created to guide better deployment of AI Justifiability Accuracy & Bias Internal & External Outcome Explainability Interpretability Align to our Ethos
- 23. Government Systems Designer Research Data Vendor AI Model Service Vendor Platform User Environment And it becomes more complicated... Who is accountable now?
- 24. AI & Fairness Is the data used a fair representation of reality. Is our model having Unintended Consequences, Systemic Issues?
- 25. AI & Transparency Strong evidence on the accuracy of the output for high-stake decisions. Interpretation- why model output is counter- intuitive & do I trust it?
- 26. AI for Compliance Right to an explanation if receiving an adverse decision Why did we decide an unpopular decision?
- 27. AI for Bias Ensure that people are not being unfairly or unknowingly excluded
- 28. AI for Generalization Ensure that the right model is used for our business objective (Concept Drift)
- 29. Managing Enterprise AI Source: https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/getting-to-know-and-manage-your-biggest-ai-risks
- 32. IEEE P7003TM Standard for Algorithmic Bias Considerations •IEEE P7000: Model Process for Addressing Ethical Concerns During System Design •IEEE P7001: Transparency of Autonomous Systems •IEEE P7002: Data Privacy Process •IEEE P7003: Algorithmic Bias Considerations •IEEE P7004: Standard on Child and Student Data Governance •IEEE P7005: Standard on Employer Data Governance •IEEE P7006: Standard on Personal Data AI Agent Working Group •IEEE P7007: Ontological Standard for Ethically Driven Robotics and Automation Systems •IEEE P7008: Standard for Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems •IEEE P7009: Standard for Fail-Safe Design of Autonomous and Semi-Autonomous Systems •IEEE P7010: Wellbeing Metrics Standard for Ethical Artificial Intelligence and Autonomous Systems Source: https://doi.org/10.1145/3194770.3194773
- 33. Artificial Intelligence & Society Fireside Chat LUIS F. GONZALEZ