1.2: What is AI, and why are people talking about it so much?
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)“AI” may call to mind science fiction images of robots that seem alive. It is often represented in software with a star or sparkles that suggest fairy dust.
But current systems that get called AI are not alive, and they are not magic. Their behavior can be accounted for by looking at how they were constructed.
Kate Crawford, author of The Atlas of AI, considers the term “artificial intelligence” itself to be inaccurate. She argues that the software that gets called “AI” is really not intelligent and not artificial either, given how much human input it requires. Software developer Simon Willison has suggested we call it “Imitation Intelligence” instead.
Computer scientists have been trying to develop mechanical simulations of human intelligence since the 1940s using a range of techniques. Excitement about AI in the 1950s and 60s was followed by an “AI winter” when funding dried up because early enthusiasts had overpromised and underdelivered. AI development, however, continued through the 80s and 90s. New techniques and greatly increased computer processing power led to advances in “machine learning” systems that train on data to be able to replicate patterns from that data.
By the 2000s, these systems came to underpin many of the ways we interact with information, including social media and internet search. The invention of a technique called transformers at Google in 2017 paved the way for today’s “generative AI” that can generate sophisticated though often flawed text, images, sound, and video. Launched in November, 2022, the chatbot ChatGPT raised popular awareness of the degree to which these systems can respond plausibly to human requests.
There’s plenty of disagreement about exactly how useful today’s AI is and how much it will change our work, our economy, and our day-to-day lives. There is also disagreement about how much better AI is likely to get both in the short term and the long term and whether it poses a significant threat to human life. Yet it seems clear that, as Gabriela Ramos of the United Nations Educational, Scientific and Cultural Organization (UNESCO) puts it, "These general-purpose technologies are re-shaping the way we work, interact, and live.” The United Nations has called on all states to “develop and support regulatory and governance approaches and frameworks related to safe, secure and trustworthy use of AI.”
There is growing agreement that we need greater public understanding of their capabilities and harms and broader participation in shaping these systems. A U.N. resolution adopted March 21, 2024 calls for “more cohesive, effective, coordinated and inclusive engagement and participation of all communities… in the inclusive governance of safe, secure and trustworthy artificial intelligence...”
Both teachers and students need to learn about AI, and college classrooms can be a space to engage with AI with curiosity and skepticism to prepare us to play a role in shaping its future.
Further reading
- Artificial Intelligence Definitions from Stanford Human-Centered AI
- WTF is AI? By Devin Coldewey, TechCrunch
- General Assembly adopts landmark resolution on artificial intelligence, UN News