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100 Days of Artificial Intelligence

100 days ago I decided to write one article about artificial intelligence every day for 500 days.

The highlights of this goes far beyond writing and in this article I will mention the benefit of thinking aloud;

I have reached a milestone and I am proud that I managed to take this small step towards understanding artificial intelligence better.

The immediate benefit that I thought about when writing regularly was becoming a better writer.

Now that I have written regularly for 100 days I do in no way think that is the greatest benefit I have received.

请教别人一次是5分钟的傻子,从不请教别人是一辈子的傻子— Qǐngjiào biérén yīcì shì 5 fēnzhōng de shǎzi, cóng bù qǐngjiào biérén shì yībèizi de shǎzi I

Yet I feel less foolish for having started to ask such a wide range of questions to this technological development while learning programming alongside different subjects in the field of social science.

Thinking aloud while reading and doing has clear benefits I will outline a few that in my experience is contributing to a learning process: Wanting to become a better writer can lead to so much more than grammatical correctness or textual flourish.

I have been so lucky and fortunate to experience what writing can be beyond my immediate expectations and for that I am grateful.

I spent the first 50 days considering a general approach to artificial intelligence writing about everything I could find.

The next 50 days I have spent focusing on AI Safety attempting to connect thoughts from this area to that of the climate crisis.

Along the way I have without a doubt felt worthless or like an idiot several times over, at times in passing.

Discovery within the lack of clarity makes it exciting every day when I write, uncertainty is in some sense a certainty.

不怕慢, 就怕停 — bù pà màn, jiù pà tíng Understanding takes time, and I am not done yet.

I have met several researchers that have studied artificial intelligence almost since before I was born or has been programming actively for a lifetime.

Academics and professionals I appreciate have imparted their learnings to me and I will do my best to carry this forward and contribute with everything I am to society.

It is strange to attempt reducing 100 articles down to two paragraphs, but I did my best and I hope it is worth something to you.

I am working on a small project to compile these learnings in a better format that should be announced soon.

100 days dedicated to machine learning for social scientists with qualitative as well as quantitative methods sounds like a fun challenge that I want to undertake.

Exploring code repositories and looking through some Python code every single day for the next 100 days will not make me a great programmer, however it will make me a slightly better programmer.

If you in this context going forward feel disappointed with my writing and that my articles are not at the level you feel necessary I apologise.

You can obsess over your lack of knowledge on a topic, being almost sure that someone is talking about your writing unfavourably.

When reaching a milestone it is customary to thank someone, and there are plenty of people that has made this learning experience rewarding.

I want to thank my fellow students for challenging my assumptions and my professors for questioning the foundations of my ideas.

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Humanity and the Benefits of Artificial Intelligence

What’s important is that you have a faith in people, that they’re basically good and smart, and if you give them tools, they’ll do wonderful things with them.– Steve Jobs: Rolling Stone Magazine, 1994 In the nearly 20 years since I started medical school, I’ve seen the practice of medicine undergo a wholesale technological transformation.

Because the days of sprinting on rounds to get ahead of the white coat phalanx, pull down a cabinet and open a three-ring binder chart to the next blank page before the intern reaches the door ended a decade ago.

Today’s medical students are instead both blessed and cursed with EMRs and patient care technologies that track and trend every aspect of the inpatient and outpatient course, demanding hours of tedious, field-driven data entry while yielding treasure troves of mineable new information.

RELATED: The Doctor-Patient Relationship Is Shifting: Here’s How One of the most valuable lessons I learned in medical school, residency and fellowship training was how to differentiate “sick” from “not sick” and “toxic” from “not toxic.” It's a skill that requires seeing thousands of patients one by one, each with a unique constellation of symptoms, all taking slightly different trajectories in the courses of their illness.

The key benefits of artificial intelligence are grounded in this ability to continuously comb the EMR, training on past patients’ trajectories in the same way clinicians are trained and hone the lenses of their own prescription glasses, patient by patient by the millions.

Used in real-time, artificial-intelligence-driven models can predict impending doom by aggregating every bit of information produced by network-connected vital signs monitors, notes, labs and anything else captured by an EMR and predict looming disaster before it happens.

However, to fully realize the power and benefits of artificial intelligence in patient care technology we have to (as Simon Sinek would say) start with “why.” Our central purpose in designing, developing and deploying artificial-intelligence-based patient care technology solutions must be grounded in helping clinicians return to their patients’ bedsides (be they at home or in hospital), and serve them with more connected information, more upstream interventions and more time to spend with the patients who most need their human bond.