Ms. Kanubala holds a master's degree in Mathematical Science with a specialization in Big Data and financial mathematics. She is currently enrolled in the African Masters In Machine Intelligence program in Ghana. Her research interest is in the applications of machine learning algorithms in the development of robust credit scoring models. Ms Kanubala holds a firm believe that, one learns better as you teach others and as such, she has a Youtube channel where she teaches machine learning enthusiasts more about the subject.
She is a proficient user of python for machine learning. Aside this, she is the co-founder of a non-profit organization called Women Promoting Science to the Younger generation. She is a recipient of several awards and grants including the Mastercard Foundation scholars grant, Alumnode grant from Germany and MIT Prize and google awards during Indaba in Kenya and Indabax Ghana respectively. Ms. Kanubala was also voted among the 20 Most influential people in Northern Ghana, STEM Category. She envision a future where people will be assessed based on their skill set rather than their gender.
Fun Fact: She loves to travel around the world, sing and dance.
Thank you very much Aseda for the introduction. First of all, I should say it's my great pleasure to be invited as a resource person for this discussion. The choice of this topic is a very interesting one which has sparked a lot of different debates on different platforms.
Personally, I wished we could all meet physically and discuss this. Unfortunately, the circumstance the world and our country, in particular, finds itself makes it impossible to do.
But I hope that once this pandemic is over, the organizers could look into putting together something of that sort. Once again, it's a pleasure to be here and I hope we have a fruitful discussion.
Yeah sure, when the pandemic is over, we would surely have some fun meetups. Thanks for your time this evening. You have an interesting and inspiring profile.
What one word would you use to summarize who you are?
Errrrrm I should say Ambitious
Some of us heard about Machine Learning just a few months if not weeks ago, but you are already doing a Master's program in it. When did you hear about it and how did you get into Machine Learning?
Well, in 2017, after I finished my national service as a TA at the University for Development Studies. I gained admission into AIMS( African Institute for Mathematical Science), Senegal to pursue Mathematical Science. In AIMS Senegal, students could specialize in 3 areas thus; Big Data, Financial Mathematics and Computer Security.
So once I arrived on campus, I was sure I was going to specialize in Financial Mathematics because I already had a background in that area. Additionally, I did not know anything about coding and so I was trying to avoid any field that was going to force me to do anything with code. Unfortunately for me at that time, but fortunately I would say today, AIMS-Senegal insisted all students specialize in at least two areas and that meant having to take a second major. Now I didn't have an option than to face my fear, so I began reading generally about what Big Data was and we had some introductory lectures about the field and the career opportunity that came with it. From my research, I began developing interest gradually in the field and this has brought me to where I am today. I should say, it's one of the best decisions I probably have ever made with regard to my career. Essentially, I have been in this field since 2017 ( roughly 2 years and some months now).
Wooow, AIMS Senegal, then I'm sure you can speak French.
Errrrrm I am still learning not fluently but can find my way out
Kindly tell us a bit about Master's education, it is difficult/challenging or it's a ride in the park?
The first thing I always tell people is that everything in this world is challenging, it only takes passion and interest in that particular thing you do that will make it easy for you. So to answer your question, a master’s education is difficult and a challenging one, but you need to know why you want to do it in the first place and that will make things easier for you. Also, knowing where your interest lies will also be very important.
Would you encourage women who are interested in Data Science, Machine Learning or AI to get a Master's or higher degree or to secure a job in the field without a higher degree?
Getting a master's degree will again boil down to what you want to spend the rest of your life doing. I acknowledge the fact that some of the ML positions that have been advertised sometimes require people with at least a master's degree or other times a PhD degree but this does not always apply to all programs. If you are interested in this field, I will first advise you to identify if you want to go into academia or industry. In the event, you want to go into academia then definitely a master's degree is a must-have and later on a PhD. Otherwise, if you want to go into the industry, getting more certifications and working experience on a lot of projects always does the magic. You will need to get your hands dirty on datasets, keep your git-hub account active and share your works with the others. Good places, to begin with, will be Zindi or Kaggle platforms. Also, you could try to take some certifications from Microsoft, IBM, etc. Certainly, some industries will prefer people with professional certification than even a master's degree. But hey, you can get hired and earn money for as long as you want. But at some point, you may just go have that master's degree so that you can fill in certain positions in the company. Otherwise, someone else with that degree with little experience may come and be given that position.
Otherwise, I believe getting a master's degree will largely depend on your career goal, go for it only when you think is necessary otherwise don't worry your head about it.
Wow, this is very eye-opening. I'm sure a lot of people have not looked at things this way. I'm sure those of us interested in the field would start examining ourselves to see what path we want to take. Thanks for that profound point made. So you have a YouTube Channel at youtube.com/channel/UCUfUdL3LvUrFIPwOLqZZ9yA.
What motivated you to start your channel?
I have a firm belief that we learn better when we teach others. As such, I am always more than willing to teach others when I can or have the opportunity. So after I got admitted into AMMI, one of the main things Dr. Cisse (Google AI Head, Accra) always encourages us to mentor others. He says it would have been his greatest wish to be able to have AMMI in almost all African countries so that students would be able to get the opportunity to gain the required skills to solve the problems facing Africa. Unfortunately, this is not possible now, the other way to achieve that will be through the few students who are able to receive this training, once we are able to also pass on knowledge to others with time, lots of other students will also have the opportunity to learn. I thought about all of these and asked myself how I can reach out to people interested in the field. I thought about having a blog, channel or even beginning an organization in doing this but later decided on a youtube channel.
Essentially, I began the channel for these two main reasons:
To ignite the interest of machine learning among interested students by explaining the concepts as simply as possible.
To share what I learn and in so doing, learning as well.
You can subscribe to my channel by the way. I am currently still deciding on a channel name so ideas are welcome
Nice, we will surely subscribe. You were voted among the 20 Most influential people in Northern Ghana, STEM Category. Can you share more on what you do in STEM up North?
Aside from my interest in machine learning, another area I spend most of my time is in promotion of STEM. I went to a girls school for my high school education and for the elective maths class for instance we had very few students. I don’t remember the actual number but we were about 11 in my class out of the 30+ students in the class. I am very sure more than 80% of the students would never have done core math if it was not one of the core subjects they needed to enter tertiary. Moving forward to my class in AIMS-Senegal, we had roughly about 9 girls out of the 36 students in my class. From my educational experiences, I have come to realize most often students fail to understand the importance of maths and some others find most of the maths courses they do irrelevant and believe they may only end up as teachers.
Identifying this, I, therefore, decided to dedicate some part of my time in this course, so I co-founded an association called “Women Promoting Science to the Younger Generation” last year Feb in Senegal. We have since organized programs in Ghana and Senegal.
Again, I happen to be an alumnus of the Heidelberg Laureate Forum and we have an alumni network called AlumNode. Through the alumni network, I co-lead my team to write a proposal for funding to organize an international conference on “Breaking the STEM Gap in Rural Africa through Advocacy and Communication”. The conference sought to connect high school students to top researchers in the field of mathematics and science. During the conference, we had mentoring sessions for these students to ask questions and seek career guidance.
Additionally, we received mathematical leaflets on practical applications of mathematics from the American Mathematical Society which we shared with the students.
Additionally, as a Mastercard Foundation scholar alumnus, I was one of the scholar’s research fund recipients to conduct research in “Increasing Women in STEM transition into Tertiary Education”. This research was conducted both in Ghana and Uganda and I co-led the team to complete this research as well.
These are some of the few STEM activities I have been engaged with over time and I do this not because I wanted to be recognized. I do this because I LOVE to do this, it gives me fulfillment to know that I contribute to the success of someone.
I want to see a future where each person is able to succeed in whatever they are passionate about, so when I have the opportunity to help I willingly do it. I always keep in mind that I got to where I am today because others gave me their shoulders to step on and so I will freely offer my shoulders for others to step on to move forward. Together we succeed !
Wow, this is commendable. Now before going to the main topic for discussion, can you please tell us the difference between Data Science, Artificial Intelligence and Machine Learning?
Very good and interesting question. These buzzwords have become really popular these days such that everyone seems to either be talking about incorporating it into their work or probably already putting this in practice. And with the increase in their popularity, we tend to find different definitions and understandings of these terms. So I am going to answer this question based on what I have come to understand about these terms from the knowledge gained over time.
Beginning with data science; the first thing to understand about this field is that it is an interdisciplinary field and as such it combines the domain expertise from mathematics, statistics, computer science and a field of expertise( health, agriculture, finance, etc). It involves the ability to process the data, understand data and make insightful decisions from it to make business decisions. Overall, a data scientist should be able to identify and ask relevant questions, process answers to these questions and be able to effectively communicate their findings that will be essential to the business.
I would like to define what AI is before I move on to talk about machine learning. AI involves building or developing machines that perform tasks that involve some high level of human intelligence.
Machine learning on the other hand and in simple terms seeks to train machines from data to be able to learn and make predictions without being explicitly programmed. This has been used in a series of places to either make faster business decisions or automate redundant tasks that humans would have used several hours to do.
We need to note that machine learning happens to be a subset of AI but as AI seeks to develop technologies that can stimulate human behavior, machine learning involves machine learning from data. It is okay to confuse these terminologies because even today some experts use AI and machine learning interchangeably. However, if you have to give a high scientific talk on this then it will be prudent to get out the differences clear.
Can you please tell us some of the advantages/benefits of AI and some disadvantages/challenges you think that it brings into the society.
AI over the years has proven to be efficient and effective and still holds strong future prospects in different areas. There are several advantages but I will want to mention just 2 of them;
Firstly, is constant availability, in most institutions the average working hours for employees are usually 40 hours per week equivalent to 8 hours per day. And this 8 hours per day even includes breaks, and sometimes monthly leaves, and ill-health. AI systems never get tired or sick or need to go on break as humans. AI systems are able to function and provide results 24/7. For instance telecommunications such as MTN, Vodafone etc are getting more AI systems to handle customers' inquiries and issues anytime.
The second and probably one of the most important advantages of AI is faster decisions. Using AI developed systems alongside the expertise of humans can help us make faster decisions. AI has been used to make faster decisions ranging from health care to financial institutions. Currently, with the issue of the COVID-19 pandemic, China uses CT image analytics solutions for mass testing. Also, medical imaging is used in detecting abnormalities in the lungs of patients.
On the other hand, AI is good, everyone is talking about, everyone wants to include it in their business but everything has both its good and bad sides. AI is no different and certainly presents some challenges or disadvantages.
The one major challenge of AI has to do with the availability of data. Access to good and quality data is one that helps to make AI systems learn and generalize well to perform the task they have been trained to do. However, it's a major problem getting access to good and quality data at the moment, most often we work with data that is probably inconsistent and unable to provide solutions to problems that businesses are looking at creating value from.
Another challenge is the unavailability and shortage of experienced scientists. From a LinkedIn workforce report in August 2018, it indicated that more than 150, 000 data scientists' jobs are going unfilled in the US. Also, research has shown that there is a 29% increase in demand for data scientists year by year.
Interesting...So with the knowledge of both the benefits and challenges of the application of AI, do you think AI is going to do us more harm than good? Speaking in the African context, do you believe that AI could one day get out of hand and extinguish all humans from the earth?
I believe AI will do us more good than harm. Though I have read and heard people have heated arguments about how AI is going to leave a lot of people unemployed. This I do not agree totally with, AI systems are deployed to automate most of the work we do now, certainly other forms of jobs will be created. The only thing people will need to do is prep themselves up with the needed skills to fill those new job openings. I.e, in the past before sending a message to someone in a different city, you had to write a letter and find someone visiting that city to have your message delivered. Few years down the line, technology birthed mobile phones, which later were connected to the internet and made it easy for people to send messages via emails and other social media outlets. Most of these telecommunications that have been borne as a result of this tend to employ millions of people today. It made it easier to send and receive important information within seconds thereby improving decision making processes and creating a strong bond between family or co-workers.
AI extinguishing all humans from earth?
Hahahahha interesting, I am afraid I don’t believe this. Yes, the current AI system has been able to complete tasks that sometimes leave us astonished but I don’t think that it can one day get out of hand and extinguish all humans.
Humans are the ones who program these systems to be able to do what they do, how then do these systems later be able to extinguish all humans.
So you are saying that even if AI would cause us harm, it would be humans who would be behind this?
I am sensing something fishy! you want me to admit AI can cause harm.
Not exactly. Because you said "Humans are the ones who program these systems to be able to do what they do, how then do these systems later be able to extinguish all humans" I'm thinking that, then maybe some wicked people may intentionally build systems to cause harm.
Well, that is possible but with a probability close to 0, however, in the case that unlikely event happens, we will still have some humans on earth. The ones who built those AI systems.
Let's say all AI engineers decide to be ethical and only build AI for good and to help solve sustainable development goals, is there still a possibility that AI systems through Machine Learning may learn some wrong things and begin to misbehave?
Well, that is possible but with a probability close to 0, however, in the case that unlikely event happens, we will still have some humans on earth. The ones who built those AI systems..........
I won't say they will " misbehave" but then they may not be able to accomplish the task they have been programmed to do perfectly. And in that sense, they will only learn from their experience and do better in subsequent tasks. Generally, these AI systems learn better from experience, they fail, receive a reward or punishment then learn from it and only get better.
Oh okay, so it means that, it's more of garbage in, garbage out. If they are given good data to learn from as their experience, they would produce good/expected results. If not, then they would not perform as expected?
I'm sure we are all aware of how debatable the topic for discussion is but we wanted to know what your thoughts were on this and I think you have shared that.
Questions from Participants
Not a question. I just want to appreciate you and Miss Kanubala for this session. Thanks for being so helpful tonight Miss Kanubala. You're an inspiration really.
I am blushing Miss Lily Botsyoe, thank you very much and I am glad for the opportunity given.
What are the requirements to pursue Ms degree in ML or AI or Data Science?
For most institutions, a good 1st degree in Mathematics, Statistics or CS can get you admission. Other institutions are also open in admitting students from different backgrounds but those are made on the condition that the students have taken introductory courses in linear algebra, calculus, and probability as these are the foundation in understanding anything in this field.
In your opinion, do you think learning AI/ML at an older age can make one quite unsuccessfully looking at the fact that it requires more time and lots of learning.
Have you met older people start studying ML and how's the performance as compared to younger ones, let's say people above 35 being the older class?
The first thing for me is that age is just a number and one is never too old to pursue his or her passion. So if you develop an interest in this field later on in life just go for it. Currently, there is a lady with a PhD degree with us in AMMI, this is someone who already has the highest degree possible but because of her passion and interest, she decided to pursue it and is doing quite well. Hence for me, age should not be a decisive factor, interest and passion is what your DRIVE should be.
Thanks for your questions ladies and thanks for your answers Miss Kanubala. Any final words for us?
My last advice; having digital skills and the ability to code will in the future not be about interest but a requirement in order to be employed. As such, it would do you so much good if you can now begin to get involved in evolution. Also, never be scared to put yourself out there for consideration. Job search, the opportunity for schools, application for conferences, etc.
Send in your applications, the worst thing that can happen is for them to REJECT you. Never stop dreaming! I wish you the best of luck in all you do and please do stay safe. I hope to meet most of you in person after this pandemic so I can get to know more about the interests of you all. Thank you once again for the invite and it was a pleasure to be here.
This session was facilitated by Aseda Owusua Addai-Desseh