DAYMN — 26 Sep 2021
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September is almost over, and the last 3 months of the year are upon us already! Time flies indeed. Here are the top 5 articles from this past week — please do share your feedback & thoughts!
1. First rule of ML : Start Without ML
After gaining a lot of attention and discussion on HackerNews, this article summarises that oft-discussed but never formalised agreement among the older guard of data scientists/analysts — Machine Learning is not the hammer for all your data nails. Sometimes — rather often times — the easiest and simplest data cuts would solve 90% of your problems, rather than having to throw the data into an ML void.
This article from Eugene Yan resonates on so many levels with me, having seen the recent trends where people start with import scikitlearn to any problem at hand. Must read among all the articles this week!
Call out? Machine learning is cool, but it requires data. Theoretically, you can take data from a different problem and then tweak the model for a new product, but this will likely underperform basic heuristics. If you think that machine learning will give you a 100% boost, then a heuristic will get you 50% of the way.
2. Headless BI — the new frontier of BI?
BI is dead, is often the war cry that all of us have heard over the last decade. But still, it is one of the constantly growing product areas in the data ecosystem — so what gives? There has never a good formulation for what is needed to overcome traditional BI and what needs to be true, to ensure that it can stick and grow. Anyone who has read this newsletter, knows of my soft spot for evolution in the BI space, given how critical it is for a business.
This article makes a great attempt at describing that “what needs to happen next” quite well, without going into too much of the AR/VR jargons and fantastical imaginations.
Call out? The core criteria of a compelling solution are:
- Easy to define metrics, without writing code (SQL)
- Metrics can be used flexibly across BI visualizations, SaaS integrations, and an API
- Metrics can be queried in real-time and at high enough scale to power automation like email triggers, product experiences, etc.
3. DIY — Build your own NEST/RING cam without giving up your data
If you are into DIY and want to play with a Raspberry Pi, to build something worthwhile — here’s a small useful project that helps you build your own facial recognition camera to identify your friends at the door.
https://www.tomshardware.com/how-to/facial-recognition-doorbell-raspberry-pi
4. UN’s clarion call of AI’s risk to privacy
UN is known to make geo-political statements and maintain that all together fragile peace in this post-nuclear world. However, when the UN Human Right Commission comes out and makes a massive statement on the risk of AI systems to human privacy — it is high time for businesses and governments to sit up and take due notice.
UN High Commissioner for Human Rights Michelle Bachelet on Wednesday stressed the urgent need for a moratorium on the sale and use of AI systems that pose a serious risk to human rights until adequate safeguards are put in place. She also called for AI applications that cannot be used in compliance with international human rights law to be banned.
https://www.ohchr.org/EN/NewsEvents/Pages/DisplayNews.aspx?NewsID=27469&LangID=E
Call out? Artificial intelligence can be a force for good, helping societies overcome some of the great challenges of our times. But AI technologies can have negative, even catastrophic, effects if they are used without sufficient regard to how they affect people’s human rights. The authors call for:
- A ban on systems that pose acute risks to human rights such as real-time biometric identification.
- A moratorium on algorithms that determine a person’s eligibility for health care until regulations are in place.
- Guidelines, independent oversight, and laws that protect data privacy.
- Mechanisms such as explainable AI that would help rectify AI-enabled abuses of human rights.
- Ongoing monitoring of AI systems for potential threats to human rights.
5. Changing the Math Culture
Wrapping up the newsletter with a heart-warming, feel-good, true heroic story about one Math professor, who tried to make Mathematics an inclusive and welcoming space for those from the fringe and ethnic minorities. A lot of culture puff pieces are written off business leaders, but sometimes these small victories by normal humans make such a massive difference.
Without giving too much away, this one will be worth your time.
https://www.theatlantic.com/education/archive/2021/09/bias-math-sexism-racism/620207/
Call out? Mathematicians frequently use phrases like It’s obvious or It’s easy to see, which can be profoundly discouraging for a student who does not immediately find a concept simple. In math, grappling with extremely difficult problems is part of the learning process. It’s especially important to make sure that students are not discouraged during early challenges — what’s hard to see now may become easier in time.
Have a wonderful week ahead everyone, hope at least one of these articles is exciting reading material for you, and made you think for a moment
