07/24/2025
(REAL) ARTIFICIAL INTELLIGENCE
by Tony Lamair Burks II EdD
I’ve been reflecting on how many people treat AI like it just showed up yesterday with ChatGPT, when the truth is—it’s been around us for decades. We’ve just gotten used to it working quietly in the background.
Think about it:
When Amazon started recommending products you hadn’t searched for but somehow needed—that was AI.
When Gmail suggested full sentences to finish your emails—that was AI.
When Netflix started knowing your taste in movies before you could explain it—that was AI, too.
Voice assistants, smart maps, fraud alerts, digital photo albums that recognize faces, even vacuums that learn your floor plan—it’s all been AI.
What’s different now is that these systems are starting to talk back, generate content, and feel more like collaborators. That’s what feels new. But the intelligence itself? It’s been here—learning, adapting, working invisibly.
We’ve been interacting with AI for years. The current moment just makes it harder to ignore. The real work now is figuring out how we show up with intention, clarity, and ethical awareness in how we engage these tools—and how we prepare others around us to do the same.
For context, here’s a timeline that helps put it all in perspective:
A Timeline of AI and Computing: From Foundational Work to Today
1940s–1970s: Programming Pioneers and Automating Logic
• 1943–1958 – The West Area Computers, a team of African‑American women including Dorothy Vaughan, Katherine Johnson, and Mary Jackson, perform critical human-computation at NACA Langley.
• 1949–1960s – Dorothy Vaughan, a West Area Computers supervisor, teaches herself Fortran and supports the transition to electronic computing.
• 1955–1989 – Annie Easley serves as a human computer, then programmer at NASA, contributing to battery research, hybrid vehicle modeling, and the Centaur rocket.
1950s–1960s: Foundations and Human Computing
• 1950 – Alan Turing introduces the concept of machine intelligence in “Computing Machinery and Intelligence.”
• 1956 – “Artificial Intelligence” is officially named at the Dartmouth Conference.
• 1959–1969 – Katherine Johnson, mathematician at NASA, performs hand-calculated orbital trajectory computations for Mercury and Apollo missions—foundational to aerospace and early computation.
• 1966 – ELIZA, an early chatbot program, is developed at MIT.
1970s–1980s: Rules-Based AI and Early CS Advances
• 1972–1980s – Expert systems (MYCIN, DENDRAL) emerge, applying logic to medical and scientific domains.
• 1969–1972 – Clarence “Skip” Ellis, the first African-American to earn a CS PhD, contributes to collaborative software.
• 1981 – Deborah Washington Brown becomes the first Black woman with a U.S. CS PhD.
• 1982 – Marsha Rhea Williams earns a CS doctorate and advances database technologies.
1990s: AI Goes Mainstream in Infrastructure
• 1994 – Credit card fraud detection systems begin using AI.
• 1997 – IBM’s Deep Blue defeats chess champion Garry Kasparov.
• Late 1990s – Spam filters, office autocorrect, and grammar checkers integrate AI logic.
2000s: AI as Everyday Technology
• 2001 – Roomba introduces AI-based vacuum navigation.
• 2002 – Amazon launches AI-driven product recommendations.
• 2006 – Netflix launches personalized recommendation engines.
• 2007–2009 – Smartphones incorporate predictive text and facial recognition.
2010s: The Era of Large Scale AI Applications
• 2011 – Siri debuts as a consumer-facing voice assistant.
• 2012 onward – Deep learning transforms image recognition, influencing healthcare and automotive industries.
• 2014–2016 – AI powers news feeds, targeted ads, customer-service bots, and robo-advisors.
2020s: Generative AI and Ethical Leadership
• 2020 – OpenAI releases GPT‑3, enabling advanced text generation.
• 2021 – Multimodal AI models combine text, vision, and speech.
• 2021 – Timnit Gebru is dismissed from Google after publishing critical work on AI bias; she then co-founds the Distributed AI Research Institute.
• 2022 – ChatGPT reaches 100 million users within two months.
• 2023–2025 – Stephanie Dinkins explores AI equity through art; Adji Bousso Dieng advances probabilistic deep models; both are influential voices in ethical AI.
