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Leaving the underground
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NIGERIA IS NOT SAFE
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Q&A Sessions with bright African minds across the globe.
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Recent Sessions with some of Africa's brightest minds.
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HR Manager @ Pernod Ricard Western Africa
Doctoral Student @ MIT
Senior Writer @ TechCabal
Creative Director @ Thalia Bespoke Nigeria
Senior Digital Communications Analyst @ Oando Plc
Educator @ Covenant University
Managing Director & Computer Science PhD Student @ The Diasporic Group & Cornell University
Senior Lecturer @ The Technical University of Kenya
International Criminal and Human Rights Lawyer
Personal Brand Therapist | Bus Consultant | Relationship Counsellor | Content Creator @ NEST Consolidated
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Top answers from some of our sessions.
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I think that often times people assume that one's identity as a black women is by default interwoven into one's academic experiences, and while that may true, I never believed that the marginalization I face based on my identity meant that there was something I could not achieve. Quite frankly, someones racism or sexism towards me is their own problem, and over time I've become immune to it. Additionally I believe the glass ceiling is a metaphor people put on us that inadvertently gives some people imposter syndrome. To me, there are no glass ceilings. I know that if I'm able to build technology solve problems for many people, and advocate for myself while doing it, I'll be able to have whatever impact I want on the world and gain recognition for doing it. Obviously I've faced misogynior in academia, and you'd be hard pressed to find any black woman at an institution with billions of dollars at their disposal to to have been shielded from that. But numbers can't be denied, and when you walk into interviews, proposals or pitches with compelling data, concise arguments and confidence, it's often hard to be ignored. That being said, we have to acknowledge that there are very few people in general in this field. Our lack of representation as black women doesn't mean that we aren't capable, just that we haven't been shown what we can do. Consequently I believe that helping others see their potential is the greatest way I can share and create value with my knowledge, whether that be through building human-centric technology that focuses on bringing value to a user personally, or inspiring others to see their own skill solve important problems themselves.

Ifueko Igbinedion
Doctoral Student @ MIT
I think this is a bit dangerous. Attempting to ascertain sentimental correlations and apply them to huge financial decisions may work in certain contexts and you could definitely train a model with 99% training accuracy on this task, but future situations that are dependent on complex human action can never be adequately represented by a numerical parameterization and a finite state machine. If the model is not large enough, we will not learn all the possible combinations of interactions. If it is too large, then we only learn the context of our training dataset. That being said, you could do both and get good results during training. Personally, I do not have extensive NLP experience or Bayesian experience in production, but their fundamentals suggest that they would learn this type of model well independently or in conjunction. Naïve Bayes is good for state estimation-based decision making, and NLP can be used to model language and extract sentiment. However, these models depend completely on the input dataset that one utilizes, and the chosen labels (if using a supervised method) that are often subjective. Using data from the internet is also dangerous because it is next to impossible to have humans annotate every piece of training data without spending a large amount of money, and learning from problematic input data can lead to problematic situations.To make this less vague, take the 2016 example where Tay, a chatbot made by Microsoft and trained on Twitter data, became extremely racist in less than a day of online training (https://twitter.com/geraldmellor/status/712880710328139776). Attempting to determine causation in a data driven sense is a slippery slope, and until AI solves the data-driven generalization problem (which I believe may be never) I wouldn't build a system like this in production until I could guarantee significant human supervision and have looked at the ethical implications on those who do not financially benefit from the proposed system.

Ifueko Igbinedion
Doctoral Student @ MIT
The use or existence of renewable energy is not directly related to carbon emissions. Ghana had a 3.54% carbon footprint in 2016, while Africa's global compounded carbon footprint is expected to be 3.8% by 2021. This means that Africa's contribution to the total of 76% of CO2 emissions is extremely small. Renewable energy sources are more of a convenience factor than a global concern. In remote villages, using a solar-paneled lamp at night is easier and safer than using a kerosene lamp. How much more expensive is kerosene today compared to 20 years ago? Renewable energy will not be able to replace conventional energy. Take note that the amount of fossil fuels used to manufacture an electric car's battery is greater than the amount used to drive 60 (average fuel consumption) cars over a 100km road. For a family, having a well dug within their property is safer and easier than having the kids run to the streams at night out of a rampant fear of watercraft. Renewable energy sources play an important role. How many years do we need to wait for geothermal sources? Is electricity, by the way, not derived from a renewable source? Dams are used to generate electricity from naturally flowing streams that are fed by an inland flow of water. The more living things die, the more biomass there is. Renewables will always be a question, as old as recycling and as new as 7th generation electric vehicles. I am ready to learn more from you.

Loic Bethel Dje
Youth and Apex Performance Mentor | Initiator @ PureBreedSbe
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Picking the minds of Africa's finest.
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