DataProphet is a South African, Cape Town based Consulting company that specialises in Machine Learning. I have had an opportunity to ask some questions from Bennie Leonard who is a Machine Learning Scientist at DataProphet. Thank you Bennie for the
insights.
Q. I see you are a Machine Learning Scientist at DataProphet. Where did
you study machine learning?
A. I studied computer science at the University of Pretoria. I
specialised in optimisation algorithms, with a focus on swarm intelligence. Optimisation algorithms
are a class of clever search methods and are often used to enable machines to learn
from experience.
Q. Why did you choose machine learning as a career?
A. Programming computers to learn has been a field of interest for
scientists for at least a few decades. However, over the last ten years or so,
the field has gained substantial traction in real-world applications. Machine
learning is widely used in the technology industry to perform a range of tasks,
including product suggestions in online shopping, search prediction for online
search engines, and even mastering difficult games like Go. Even so, there are still a huge number of businesses that are either
unaware of the capabilities and potential benefits of machine learning, or struggle to
understand how to apply machine learning to their unique business environments.
The enormous potential that machine learning and artificial intelligence
has to offer, and the excitement of working in a very young and developing
field, are what drove me into a career focussed on machine learning. At
DataProphet we aim to understand and fill the gap between scientific advances
in machine learning and the useful application thereof to individual
businesses.
Q. What algorithms do you apply on your job as a machine learning
specialist and why?
A. Different applications of machine learning often require unique
combinations of algorithms to perform a given task. Our expertise at DataProphet ranges
from relatively old (and commonly used) tree-based classification methods to
the most recent developments in deep neural networks. Which specific algorithms
to apply depends heavily on the scope and specifications of each individual
project.
Q. We have professionals that are well known for their work in machine
learning, who do you look up to?
A. There are many highly respected professionals in the field, but
progress rarely comes without relying on the work of other scientists.
Personally, I have deep admiration for the likes of Alan Turing, John von Neumann,
and Ada Lovelace, who played crucial roles in laying the foundations for the
science we build upon today.
Q. What is the adoption rate of machine learning in South Africa?
A. It’s hard to put a figure on the adoption rate of machine learning in
South Africa. While it is definitely increasing, we often find that businesses
are either overly optimistic, or overly skeptical when it comes to machine
learning. There is still a lot to do in terms of educating people as to what
the capabilities of machine learning are. With a better understanding of the
technology, the adoption rate will likely increase faster.
Q. I had a presentation on machine learning where I gave an example of
(FITZPATRICK,2015) article “Three Trends That Will Define the Next Horizon in Legal Research”
where he talks about machine learning as one of the trends. The question that I
got was around ethical issues when training these models. What is your take on
that?
A. As with any technology, it is important to consider the ethical implications.
Machine learning models are trained on the data that humans provide them
with. In that sense, the algorithms are general-purpose algorithms. They will
attempt to understand any data that is presented to them and the trained models
can be applied in any way we wish to apply them. Throughout history (and still
today) there are many examples of technology being used in unethical ways. It
would be naive to think that machine learning is somehow immune to this
possibility. Indeed, companies like Google’s Deep Mind and the non-profit OpenAI
have already established ethics boards to guard against the unethical
application of artificial intelligence, and rightly so.
However, the intent of
scientific research is ultimately to expand and enrich human knowledge. That
intelligence forms part of who we are is indisputable. And in our quest to truly
understand intelligence, we will undoubtedly learn more about ourselves. So we
are faced with two choices: we can either continue on this path to discover the
true nature of intelligence, while being mindful of the potentially far-reaching
ethical implications of what we might learn; or we can credulously decide that
the risk is too great and be willfully ignorant about this mysterious quality
we call intelligence, that is such a big part of who we are. We should all
choose the former.
Bennie Leonard