#168 Part 2 - Responsible AI and Personal Branding with Steve Nouri - Head of Data Science & AI
In part 2 of our interview with Steve Nouri, he speaks about AI specializations and shares his thoughts about AI innovation in developing countries.
He says that AI is quickly evolving and we’re going to see a lot of specialized people working in the AI field in bigger organizations.
Also in this episode, we discuss personal branding and its importance for a Data Scientist. Steve shares first-hand experience on how he got started with his personal branding years ago and how it helped him with his role at the Australian Computer Society.
Don’t miss this episode as Steve shares his wealth of information with us.
Enjoy the show!
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Quotes:
“So the reality is, AI is going to take more jobs than it generates. Based on my own personal opinion, that's the reality, I don't think that it's going to be able to generate more jobs than it's taking. But on the other hand, because of all the other technologies going forward, there will be jobs that we have never heard of, you know, like, I don't know, like these NFT is just going super crazy.”
“I think that there's going to be two broad big camps. One is going to be the advanced AI plus tech technology camp, where it's kind of like the machine learning engineering, we're going to have the data engineers and kind of like that evolving. Thread that obviously it's a vein, that's kind of, I think, continuing to specialize in terms of the AI side and the technology side. And then the other part is the, what you also mentioned, domain knowledge plus AI. And that's where we're going to have like, deep experts in fields.”
“You need massive stats to understand machine learning and also understand how to do analytics on data. Data Sets are not as you know, straightforward, as you can see, like the iris data sets or things that are available on different open data sets available on online. It's more complex, the business is more complex. The results need a lot of experiments and validations. And you need that kind of foundation to actually understand more about your data as well.”
”I encourage you, at the same time that you are doing your tertiary courses, start learning the latest, I guess, course from the latest quarter courses on different platforms. There are lots of free resources out there, I don't I wouldn't say that you need to pay a lot to learn these skills. But you definitely need to be hands-on before entering into these roles. “
“That's a dilemma, kind of, you will see a lot of these advertisements asking for a couple of years of experience as an entry role to a data science Pro, which is like, how can I even have it for the entry role? So I would say, internship is your best gateway into one of these entry roles.”
“From the bias and ethical perspective, that is still something that we need to be very careful, because if the, you know, having less data available from underrepresented groups, and people with you know, different socio economical background might not be as beneficial from the AI applications. And that's why we need to why we need to have these AI ethic frameworks in place.”
“ Hackathons are the best quick way to get to know people kind of, maybe find your future co founder, maybe find a lifelong, kind of, you know, friends who are sharing the same principles with you. And this is, this is a good way to actually learn from others as well, because there are usually a lot of mentors and senior professionals in the hackathons to help you deliver your solution.”
“It is not possible anymore to meet and greet everyone face to face. So you need to have some sort of digital identity social media presence too, to get known and to participate in sort of different events. And, you know, this is something that 100% will change your career, you will get noticed more, you would have more opportunities to do whatever you like.
“And your brand is going to be helpful when you are not actually actively needing it. So what is happening is like, today, you need to start it. And you need to build this asset in the long term. Don't wait until you absolutely need to have a voice.”
Questions:
07:53: What do you think about the field and in particular the specializations? What do you think AI will look like in the future? Where do you think we're, we're heading from that perspective?
11:38: If I want to solve complex business problems, and really make an impact, is it worthwhile going back to learn the foundations of maths? Or should I focus on the softer skills I already have?
14:15: What are your thoughts about universal basic income? Do you think it's inevitable due to AI?
20:45: When do you first see ACS in Australia recognizing that a science slash AI accreditations, for instance, instead of scientists have broader skills and still have to go through other accreditations, like software engineer, business analysts, etc?
22:34: What about AI innovation in developing countries, where it industry, including the internet, may not be as advanced? Do you believe that there are opportunities in the AI space in those countries?
26:49: Have you participated in hackathon? Any other thoughts or comments on hackathons?
28:15: Have you done any work or projects in the data or AI, ethics space?
29:48: Do you think personal branding is important for a data scientist?
33:34: How to use social media for data science?
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