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70 days of Artificial Intelligence

Writing an article every day for 70 days about AI

After time and writing it seems that I am slowly moving into understanding more. Attempting to understand AI is jumping into deep water, and this can be a dangerous place to be in. As such I am splashing away in a swimming pool, here with you: at/on Medium. Therefore I know slightly more than I did before, yet people seem to make the assumption that I know far more than I do (which I do not). These last days I have been writing about AI Safety, and it has been a fascinating topic ranging from the existential threat of AI to practical implications of AI in given situations.

Topics that I will be looking at going forward in the next ten days will be focused on state-of-the-art attacks within the field of artificial AI. I have been contacted by IBM and I have decided to talk to them regarding the following:

Then again to explore these three topics I will have to dive deeper into practical cyber defence. From what I have understood so far in AI Safety there is a challenge with adversarial attacks (recurrent neural network or adaptive algorithms) or poisoning attacks within machine learning techniques (altering the data set algorithms are based on).

Earlier this year Jesus Rodriguez described adversarial attacks and a common scenario in an article called Adversarial Attacks that can Make Your Neural Network Look Stupid:
“One of the most common scenarios of using adversarial examples to disrupt deep learning classifiers. Adversarial examples are inputs to deep learning models that another network has designed to induce a mistake. In the context of classification models, you can think of adversarial attacks as optical illusions for deep learning agents”

There is a page on Adversarial Machine Learning on Wikipedia. There are two attacks listed that I chose to communicate here:

Still as I have mentioned previously I am hoping over the course of the 500 days with 430 days left that I will be able to move increasingly into programming in Python and talking of maths combined with social science. This may move discussions to (an even more) narrow audience. However perhaps due to my lack of skill I may be able to communicate basic learning within the given area or my lack of knowledge so that we can engage in discussion. Either that or you have learnt more with me as a reader.

There is still very much to learn and after 70 days, as I usually say in a summary, I am still scratching the surface or operating with little understanding. It is clear that it will take a far longer time even more than 500 days (which is not that long) to get to know the field of artificial intelligence slightly better. Neuroscience, biology and the natural sciences is not even a field I have considered enough yet is emerging now in a few discussions I am having online. I have to gain an understanding in these or new friends that I can continue to discuss these topics with. Perhaps even move into this type of environment, a PhD student recently sent me a medical project that could be relevant.

Aside from this I am writing on a draft for a book project that I have thought about doing a pre-release on when I hit day 100 in 30 days. If you are interested in reading through this and giving me feedback I would be incredibly happy. Feel free to contact me directly on social media (anywhere) or write a response to this Medium post if you are interested.

Before I round of day 70 it may be suitable to tell you a few key points that I have reflected on during this time. I will recite from memory rather than attempting to give you a full breakdown of all the 70 days.

Thank you so much for following my post. Day 70 is still a milestone no matter how far I get every day is a present and I appreciate learning tidbits about such a vast topic or field that artificial intelligence is.

This is day 71 of #500daysofAI. My current focus for day 50–100 is on AI Safety. If you enjoy this please give me a response as I do want to improve my writing or discover new research, companies and projects.

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.