My last post warned against treating AI as magic. Now let’s look at what these tools can actually do.
Translation That Works Link to heading
Google Translate has improved dramatically. Ten years ago, its output was barely readable. Today it helps me collaborate with developers across Asia and Europe. Neural networks made this leap by learning from context, picking up idioms and technical terms that older systems mangled. Technical discussions now flow across language barriers, even if some nuance gets lost.
Smart Math Tutoring Link to heading
Carnegie Learning’s MATHia shows the real potential of adaptive software. Students struggling with fractions receive targeted practice, while those racing through algebra encounter steadily increasing challenges. This individual pacing is valuable in classrooms where teachers must divide attention among many students.
Medical Pattern Recognition Link to heading
AI systems can analyze large datasets faster than human experts. A 2021 University of Montreal study demonstrated this with mental health interventions; their system identified effective treatments by processing more cases than humanly possible, finding subtle patterns in the data. The same approach helps with medical imaging, where AI analysis provides doctors with additional data points for diagnosis.
Getting It Right Link to heading
Building systems requires more than technical skill. A statistical error rate of 0.1% sounds impressive until you realize it means thousands of false arrests in a city-wide facial recognition system. Hiring algorithms perpetuate discrimination, while recommendation systems push users toward extremes. The problems multiply as these systems spread.
Open source development offers one path forward. Code that affects communities needs to be shaped by those communities. The alternative is obvious in hindsight but invisible during development.
Moving Forward Link to heading
Engineering skill and careful testing matter more than hype or fear. These systems work best when we understand their limits and capabilities. Treating them as magic or menace misses what technology can actually achieve.