Data Science Insider: November 5th, 2021

In This Week’s SuperDataScience Newsletter: Hiring Your First Data Scientist. AI Will Help Grow Vegetables on the Moon. Machine Learning Pulls Insight from Cell Images. AI is Starting to Have a Big Real-World Impact. Artificial Intelligence Historian Dies. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [Hiring Your First Data Scientist]( brief: In recent years, with data science rising to prominence, hiring a data scientist (team) has become something of a priority for companies big and small all over the world. However, it hasn't all been roses and 10x growths. Mikhail Zhilkin, a data scientist at Arsenal FC, explains that it's not uncommon for the position to devolve into one of three things: a toy like a website during the dot-com bubble, a marketing tool for flashy investor pitches, or a decision justifier with no chance of actually changing anyone's opinion. Instead, he says, it should be all about bringing actual value, so he offers several pointers on the hiring process, including tips on a competitive salary and what to focus on during the interview process. Why this is important: Even if you're not in a position where you're looking to hire a data scientist for your company, you may well be in a position to get hired by one. Seeing things from a different perspective can bring you surprising insight and make you much better prepared for your next opporunity. [Click here to find out!]( [AI Will Help Grow Vegetables on the Moon]( brief: Recent developments in space technology have brought us closer than ever to the reality of long-term living in space. But producing food in an unfriendly environment is not as simple as sticking some potatoes in the ground. To help astronauts grow vegetables on missions to the moon and beyond, University of Southern Queensland (USQ) scientists are developing AI tech based on existing technology for improving crop yields on Earth. Computer vision algorithms can monitor each plant's progress and enable the astronaut to manage it in an optimal way. Eventually, robot gardeners or even 3D-printing food might become viable but even those will likely be based on knowledge gained during these first steps towards autonomous living off our home planet. Why this is important: Exploring the final frontier is a dream for many but it's not all about big rockets and space tourists. Providing basic necessities like food, water, and air will be a gigantic step in our next leap forward. It's not surprising that data science will play a large role in this. [Click here to read on!]( [Machine Learning Pulls Insight from Cell Images]( In brief: Looking at individual cells through microscopes has been possible for a long time but as with so many other fields, using data science algorithms to sift through the mountains of data has ushered in another huge wave of innovation. Anne Carpenter is a computational biologist who designed an open-source machine learning software to research cell images. What started out as a side project, "a little scrap of code to do a thing", has now been cited in over 12,000 publications and continues to provide amazing value to the scientific world. Why this is important: Anne Carpenter started out as a biologist but found towards the end of her postdoc that she would rather develop tools that help others realise their cool projects than pursue her own. Sometimes data science work can be hidden in the background but that doesn't make it any less valuable. The numerous awards Anne received for her work prove that. [Click here to discover more!]( [AI is Starting to Have a Big Real-World Impact]( In brief: Stuart Russell, an AI professor at the University of California, Berkeley, says that the field of AI needs to "grow up quickly to ensure humans remain in control". The author of a leading AI textbook from 1995 and founder of the Center for Human-Compatible AI claims that experts are “spooked” by their own success, even going so far as to compare the advance of AI to the development of the atom bomb. With a future where machines with great-than-human intelligence ever closer - estimates range from 10 years to a few centuries - opportunities, as well as threats, are everywhere. Russell believes that "the future for AI lies in developing machines that know the true objective is uncertain, as are our preferences, meaning they must check in with humans – rather like a butler – on any decision". Why this is important: A data scientist's job is complex, involved, and ever-changing. But we cannot lose sight of the fact that it is also highly responsible. While we cannot be held accountable for the entirety of the data science field, each of us needs to be aware that we are contributing to a powerful field that will change the future. And with great power comes great responsibility. [Click here to see the full picture!]( [Artificial Intelligence Historian Dies]( In brief: Pamela McCorduck wrote a groundbreaking history of AI covering the field's first 20 years, based on a number of interviews she conducted with prominent computer scientists in the 1960s and 1970s. During a time when computers were little more than "plodding sorcerer’s apprentices", she wrote about the founders of a new science who imagined tools that seemed like science fiction at the time. While implementations of data science such as speech recognition or robotics are widely in use today, back then, it took true visionaries to imagine them, and an excellent listener and communicator like Pamela McCorduck to record it. Why this is important: It has often been said that unless we know where we came from, we can't know where we're going. This is as true in AI as it is in any other field, and we are forever grateful to McCorduck for showing us our roots. [Click here to find out more!]( [Super Data Science podcast]( In this week's [Super Data Science Podcast](, James Hodson joins us to discuss the important work of his A.I. For Good organization and the areas of interest in which they are promoting sustainability and assistance on social issues. --------------------------------------------------------------- What is the Data Science Insider? This email is a briefing of the week's most disruptive, interesting, and useful resources curated by the SuperDataScience team for Data Scientists who want to take their careers to the next level. Want to upgrade your data science skills? Check out the [SuperDataScience platform]( and sign up for membership today! Know someone who would benefit from getting The Data Science Insider? 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