In 2022 if you haven't heard about artificial intelligence (AI), you must be living under a rock. When it comes to cutting-edge science and technology, Artificial Intelligence and Machine Learning are the buzzwords of the millennium.
We, at Edugraph, had the opportunity to interact with an Explainable AI Researcher to understand the impact of AI in today’s work culture, the future of AI and much more.
With 7 years of experience in data science, machine learning, IoT, and software engineering, Aditya Bhattacharya is a researcher on explainable AI at KU Leuven in Belgium. He has worked for companies like West Pharma, Microsoft, and Intel, in various capacities, to democratise AI adoption for business solutions. His book "Applied Machine Learning Explainability Techniques" recently debuted on Amazon.
1. Could you define AI in the simplest terms possible?
In my view, Artificial Intelligence (AI) is the ability to recreate the computational, cognitive, and perceptual intelligence of human beings by a computer system. So, in simple words, an artificially intelligent computer system can think and react to a given situation like a human being and understand the thought process and emotions of human beings.
2. What value can AI bring to organisations? Are there any disadvantages of using AI?
AI can supplement human abilities to enhance overall productivity and output. For organisations, AI adds significant value in streamlining operations, empowering business stakeholders for data-driven decision-making and enhancing the overall customer/end-user experience.
In terms of disadvantages, the major challenges are due to the unavailability of good quality curated data and the explainability of AI algorithms. As AI algorithms are often considered “complex black boxes”, non-technical business stakeholders and consumers of AI applications are often sceptical to use them. This lack of trust is a major concern for the AI community as it causes hindrances to adoption.
3. What is your role as an Explainable AI researcher?
The emerging field of Explainable AI (XAI) holds the potential to bring AI applications closer to end-users and increase adoption across domains. My role as an Explainable AI researcher involves working closely with non-technical consumers of AI. It includes working towards understanding the exact challenges, pain points and potential solutions for the lack of trust in AI. The goal is to improve the overall human experience in various application domains by leveraging the true potential of AI.
4. Walk us through your journey from an engineer to an Explainable AI researcher.
Well, I started my professional journey as an intern at Microsoft for emerging technology fields like the Internet of Things (IoT) and Machine Learning. I got deeply involved in AI during my second internship as a research engineer at Intel. I got to work in the speech analysis domain, particularly on a smart speaker device capable of controlling home appliances with voice commands.
Since then, I have worked in various application areas of AI and Data Science like Chatbots, Computer Vision applications, Business insights and forecasting, Cyber Security, Robotics, and others in organisations like Microsoft, Intel, and West Pharmaceuticals. I have noticed that organisations would rather work in a dull environment than adopt a new tool to boost productivity. So, I started to explore the potential issues that are holding them back.
I found that one of the reasons for consumers being sceptical about AI products is the lack of transparency offered by the systems. Consumers are hesitant to embrace AI as “they don’t fully understand AI”.
I decided to pursue a career as a researcher in Explainable AI for bringing AI closer to end-users.
Also, Read: How to become an AI Engineer?
5. Can you give some examples of practical applications of AI in our everyday lives, that may not be very evident?
There are plenty of AI applications which we all use knowingly or unknowingly every day. Almost all the applications on a smartphone are based on AI. From face, voice, and gesture recognition to automatic translations in social media applications like Facebook, Twitter, and LinkedIn to personalised recommendations on YouTube, Amazon, and other e-commerce and OTT platforms.
I rely a lot on Google applications. From Google Translate to Google Maps, all these AI-based applications are my saviours in urgency. The weather changes very frequently in Brussels. Hence, I rely a lot on weather prediction applications which use machine learning to predict varying weather conditions. In today’s time, everyone uses Google Search, which is also based on complex AI-related language models and page rank algorithms for searching resources on the internet.
6. How is the growth in AI affecting the job market and job seekers of tomorrow?
From what I have seen, AI has opened up the job market for many new roles in the last decade. Roles related to data science, data engineering, ML engineering, and business insights have increased significantly in the last few years. So, from my perspective, AI will give more opportunities for job seekers to pursue many new exciting careers other than traditional ones.
7. Do you think that AI is a threat to the human job market? What is your take on this?
No, not at all. People had the same thinking when computers were being democratised. Many political leaders were hesitant as they thought computers would take up the jobs of the common people. But fast forward 30 years, all of us have at least 2-3 computing devices that we can’t live without!
People fear what they don’t know about - and AI is a prime example. AI will only digitalise the job market and create new roles in the future. Job seekers just need to believe in continuous upskilling and should step outside their comfort zones.
8. Do technologists and engineers have a duty to think about the societal impact of AI, such as labour displacement?
Of course. Every human being should have an inherent responsibility of looking after society. I believe technology leaders are doing that. If job seekers are looking for relevant jobs, there are numerous learning resources available online through YouTube, blogs and articles, absolutely free of cost. So, I think technology leaders do consider the societal impact. But it's not just about them, everyone should actively collaborate toward solving societal problems.
9. You have been actively mentoring, instructing in forums outside of the workplace and using social media channels to provide technical knowledge to students. What is your motivation to do these things?
My biggest motivation is the urge to give back what I have received. Throughout my life, I have received a lot of help and support from my mentors and community members. Expressing my gratitude through words is not enough. So, I decided to give back what I have received through my active mentoring, community participation and contribution outside the workplace.
10. What are some hard technical skills that a student aspiring to be in the field of AI must have?
The field of AI is an intersection of many fields like computer science, mathematics and statistics and application domain knowledge (like healthcare, agriculture, finance, marketing etc.) So, students should have a good depth in computer science first, especially in topics like Data Structures, Algorithms, Programming and Software Engineering. In mathematics and statistics, they need to have a good grasp of Linear Algebra, Probability and Distribution. Specific domain knowledge comes only with active involvement in the domain. Other hard skills don’t matter as long as the selected tools can solve the problem.
11. On a different note, how do you keep up confidence and motivation in adverse situations?
I think it’s all about believing in yourself and being honest with yourself. We all have immense up-tapped potential in ourselves that we don’t even know about. Yet, everyone faces adverse situations in life, since we can only control very few things in life. Stepping outside our comfort zone enables us to be more confident. Personally, when I realised I fear being outside my comfort zone, I started making myself “uncomfortable” consciously. So, we all need to be comfortable with getting uncomfortable.
Believing in yourself that you can reach your goals makes a huge difference. It gives you more confidence. My suggestion will be to go old-school and write down your top goals in your life currently. Take time to reflect on where you are and what you need to reach your goals. Start with baby steps towards your goal until you have a clear vision of the finish line and believe in yourself throughout!
12. What advice would you give to young people who are aspiring to work in the field of AI?
Since AI is a very broad domain, it is easy to get lost or diverted. Therefore, I’d suggest picking up one area of AI and deep diving into it. Spend time creating and learning resources on YouTube, Medium, GitHub or your website! Mentor and help fellow aspirants as much as you can. Be an active contributor to the AI community. Always remember that we can all go far if we grow together!