This week, we continued working on machine learning. The most interesting development of our networks was implementing classifying images captured from a webcam. To do this, we went back to using JavaScript, and it was surprising how used to coding in Python I had gotten, even though I felt completely fluent in JavaScript not that long ago, I found myself making mistakes.

We were also introduced to the Industry folder task. Thoughts about where my career might go have always been abstract and vague, so researching what companies and jobs exist in the real world felt quite scary and like a bit of a reality check. But I’m glad this task is forcing me to think about these things.

As a part of research for the industry lab, we visited Lab Media, an organisation that supports young people who don’t always suit traditional school. They help the children to build their confidence by supplying them with a wide range of creative technologies to make projects with. I found it strange to hear about the kind of kids who go there, many having an EHCP (Education, Health and Care Plan) and not going to school, as I was like this when I was younger. I wondered if I’d be different if I had gone to a place like Lab Media, but it’s nice to know these sorts of places exist for struggling children now, even though I didn’t have the opportunity to use them.

This week’s lectures were very thought provoking. They were on the UN’s sustainable development goals, relating to creative practice with technology and Tech for Good. An exercise that was part of these lectures was trying to come up with a system to track movements of sea lions, without damaging the environment, being invasive to the sea lions or affecting the surrounding community. Trying to figure this out made me realise how hard it is to design tech for good that doesn’t have any consequences at all.