At the ReWork Retail and AI Assistants summit in London I was lucky enough to interview Kriti Sharma, VP of AI and Robotics at Sage, in a fireside chat on AI for Good. Kriti spoke a lot about her experiences and projects not only in getting more diverse voices heard within AI but also in using the power of AI as a force for good.
We discussed the current state of AI and whether we needed legislation. It is clear that legislation will come if we do not self-police how we are using these new tools. In the wake of the Cambridge Analytica story breaking, I expect that there will be more of a focus on data privacy laws accelerated, but this may bleed into artificial intelligent applications using such data. Continue reading Democratising AI: Who defines AI for good?
By now, the majority of people who keep up with the news will have heard of Cambridge Analytica, the whistle blower Christopher Wylie, and the news surrounding the harvesting of Facebook data and micro targeting, along with accusations of potentially illegal activity. In amongst all of this news I’ve also seen articles that this is the “awakening ” moment for ethics and morals AI and data science in general. The point where practitioners realise the impact of their work.
“Now I am become Death, the destroyer of worlds”, Oppenheimer
MS327 progress – not where it needs to be to do well on TMAs
It’s been a crazy month. From the lead up to the product launch at work to know it seems like I’ve been doing nothing but back to back assignments for my Open University maths degree. So much so in fact that I’ve not had time to study, but only focus on the assignments themselves. It all started back with the second TMA for M337 (Complex analysis), which was a rush job and I got a much lower score on that than I would have liked.
I then had two weeks until a computer marked assignment for MS327 and was going into this without having looked at any of the material in the book. As usual, I spent my commute trying to get through it, but barely made it a quarter of the way through before I realised I’d have to start working through the questions for the assignment. Computer marked assignments are very different from the tutor marked ones. You either select an answer from a choice of 4-6 potential results1 or by typing a numerical result. Therefore your answers are either correct or incorrect. There are no marks for method.
If you find yourself in this position, my best advice is always to do the unit quizzes. These are usually in a similar format and will get your brain in the right place for the assignment itself. In combination with the handbook and text books you should be able to follow how to get the answers from the questions, although please make time to go back and fill in the gaps as soon as you can.
Noise levels at the local soft play centre. Earplugs don’t really help – it’s so high pitched you feel it through your teeth more than your ears 😉
With the iCMA out of the way, I then had a week for the third TMA of MS327. Fortunately on the same topics as the iCMA, but much more involved questions. This was a lot trickier to pick up. With the usual standing room only on the commute, I’ve had to spend a lot of evenings trying to do this around family time and study in the excessive noise of soft-play centres… not a great environment for thought!
So I’ve just submitted the MS327 TMA online and I’m pretty happy with it. Now I have two weeks to get the M337 TMA3 done and I’m a little more nervous about that. There isn’t time to go through the study materials and answer the questions, so I’ve given myself a week to get as far as I can and then I’ll dive into the TMA and see how far I can get…
On the plus side, the OU offers substitution on your assignments, so it’s okay to have a bad one and you’ll be allocated a score that’s the average of the other three. So I can still pull up my average for M337, as long as I do well on this TMA.
This level of progress isn’t looking good at the moment…
I’m really hoping that I can get time to get these to 100% before the exams in June!
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