📘 Universal Basic Income in the Age of Artificial Intelligence

A Research Perspective on Automation, Economics, and Human Dignity

This repository contains my research paper exploring the accelerating impact of Artificial Intelligence on the global workforce and the growing need for Universal Basic Income (UBI) as a stabilizing economic policy. The paper integrates expert insights from leading AI researchers, economists, and technologists while also including my personal reflections as an AI/ML Engineer. 📄 The Societal Impact of AI and the Case for Universal Basic Income

(Clean, flowing version with expert quotes & author reflection)

Artificial Intelligence is accelerating at a pace that surpasses previous technological revolutions, reshaping industries, labor markets, and long-term economic structures. Unlike earlier automation that targeted physical labor, modern AI systems now automate cognitive, creative, analytical, and highly skilled tasks. As Sam Altman, CEO of OpenAI, stated in 2023, “Most jobs as we know them today will be transformed by AI, and many will disappear entirely” (Altman, 2023). This transformation raises critical questions about economic stability, human identity, and the future of work.

Research from MIT economists Erik Brynjolfsson and Andrew McAfee shows that technological revolutions increase productivity but tend to concentrate wealth among those who own the technology rather than those who perform labor (Brynjolfsson & McAfee, 2014). AI magnifies this pattern because it can replicate human-level reasoning at scale. Major firms—including Amazon, Meta, IBM, and numerous financial institutions—already deploy machine learning systems that automate decision-making, risk modeling, hiring processes, medical imaging, logistics, and customer support. Studies from McKinsey estimate that up to 800 million jobs worldwide could be automated by 2030 (Manyika et al., 2017). As the capabilities of AI models expand into programming, legal drafting, data analysis, and scientific research, even high-skilled white-collar fields face disruption.

Economic inequality is expected to rise as AI systems increase corporate efficiency while reducing the need for human labor. Nobel Prize–winning economist Angus Deaton argues that inequality worsens when technological progress outpaces social policy, warning that “inequality becomes self-reinforcing unless deliberate structural interventions are made” (Deaton, 2018). Without such interventions, the gains created by AI will disproportionately benefit shareholders, model developers, and large technology companies, leaving millions displaced from the labor market.

Many economists, technologists, and policymakers now identify Universal Basic Income (UBI) as a potential stabilizer in an AI-driven economy. UBI provides all adults with a guaranteed recurring income, regardless of employment status. Trials in Canada, Finland, and U.S. pilot programs show promising results: reductions in poverty, improved mental health, increased entrepreneurial activity, and no major drop in workforce participation (OECD, 2019). Elon Musk expressed similar views, stating, “AI will take over most jobs, and UBI will be necessary” (RoboBusiness, 2017). His reasoning highlights the inevitability of widespread automation and the need for a safety net that supports human dignity while enabling people to retrain or pursue new forms of value creation.

AI experts widely agree that the scale of automation will require more than traditional welfare programs. In 2023, Geoffrey Hinton—the “Godfather of AI”—warned that “AI could eliminate routine jobs across all sectors faster than we expect” and urged policymakers to prepare for mass transitions (New York Times, 2023). If society fails to act, large portions of the population may face chronic unemployment, economic precarity, and worsening mental health, even as overall economic productivity increases.

Robotics, large language models, and autonomous systems will continue to advance. While some fields—such as advanced engineering, cybersecurity, robotics research, quantum computing, and theoretical sciences—will remain deeply human-driven due to their complexity, most routine or operational tasks are on a trajectory toward full automation. The World Economic Forum predicts that 44% of all workplace skills will be disrupted within five years, largely due to AI and automation (WEF, 2023). This suggests that economic systems must shift from labor-based income assumptions to a model that supports citizens in a post-labor economy.

In my view, UBI is not just a policy proposal—it is a realistic and necessary response to the inevitable direction of AI. As someone pursuing a future in AI and engineering, I see firsthand how quickly machine learning models, agents, and automation tools are evolving. Within the next decade, I believe society will shift into a reality where most non-technical jobs and many technical ones are automated, leaving only deep STEM fields—AI engineering, robotics, physics, cybersecurity, quantitative research, and advanced software architecture—requiring long-term human expertise.

For everyone else, a stable economic system will be needed so people can live with dignity as AI becomes the primary driver of productivity. UBI is the only solution that both protects citizens and ensures the benefits of AI are shared broadly—not just concentrated among the wealthiest corporations. My hope is for a future where AI empowers humanity, and UBI becomes the foundation that allows people to thrive in an automated society.

My name is Corey Leath, and I am an AI/ML Engineer + Full-Stack Developer working toward a long-term career in advanced AI systems, Machine Learning Engineering, and Quantitative Algorithmic Research.

I am currently on a multi-degree academic pathway to become a top-tier engineer and researcher:

• 🎓 Associate of Science — Engineering Technology (Machine Learning & Design Techniques) – Completed
• 🎓 Bachelor of Science — Software Development (Web & Mobile Applications) – In Progress (11 months remaining)
• 🎓 Master’s in AI Engineering — University of Pennsylvania (Upcoming, 2026 Intake)
• 🎓 Ph.D. in Artificial Intelligence — Goal after Master’s

My mission is to build high-impact systems at the intersection of:

• AI Engineering
• Machine Learning & Deep Learning
• Full-Stack Application Development
• Quantitative Finance & Data Engineering
• MLOps + Cloud Deployment

Here are the projects that define who I am as an engineer — modular, production-minded, and deeply technical.

Tech: Python, Pandas, Numpy, MLFlow, CI/CD, Docker
Status: 🚀 Production-Ready

✔ Professional trading backtester
✔ SMA, RSI, MACD, ML-based strategies
✔ Full PyTest suite + GitHub Actions
✔ Sharpe/Sortino/MDD/CAGR metrics
✔ Modular, industry-style architecture

👉 Repo: https://github.com/Trojan3877/Algo-Quant-Backtester-

Tech: TensorFlow, Keras, OpenCV, CNNs
Status: ✔ Completed

✔ Custom CNN + transfer learning
✔ Confusion matrix, accuracy, precision/recall
✔ Real-time prediction support
✔ clean modular ML pipeline

👉 Repo: https://github.com/Trojan3877/Facial-Emotion-Recognition-System

Tech: Random Forest, XGBoost, Pandas
Status: ✔ Completed

✔ Full EDA → preprocessing → train → evaluate
✔ ROC Curve, Feature Importance, Metrics
✔ Clean ML workflow

👉 Repo: https://github.com/Trojan3877/Disease_Prediction_Capstone

Tech: C++, Python, ML
Status: ✔ Polished

✔ C++ implementation
✔ Python implementation
✔ Evaluation metrics
✔ Production-style project structure

👉 Repo: https://github.com/Trojan3877/AI-Vehicle-Safety-Classifier

Tech: C++, React Native, Firebase (Auth + Real-time DB)
Status: 🛠 In Development

✔ USC-themed real-time chat app for fans
✔ Mobile app architecture
✔ Backend + authentication
✔ Event-based messaging system

👉 Repo: https://github.com/Trojan3877/TrojanChat

Python • TensorFlow • PyTorch • Scikit-Learn
CNNs • RNNs • Transfer Learning • MLOps • MLFlow

Pandas • NumPy • Financial Indicators
Backtesting • Time-Series Forecasting • Risk Metrics

C++ • Java • JavaScript • TypeScript • SQL • OOP
System Design • MVC • REST APIs

FastAPI • Flask • Docker • CI/CD • GitHub Actions • Firebase • Linux

HTML/CSS • React Native • UI Flow Design

📧 Email: [email protected]
🔗 LinkedIn: linkedin.com/in/corey-leath
🐙 GitHub: github.com/Trojan3877

To rise above adversity and build intelligent systems that transform industries, elevate human capability, and open doors for others through AI and engineering excellence.

⭐ “Built from passion, powered by discipline, backed by AI.” ⭐