[POTENTIAL MURDER DRONES SPOILERS AHEAD]
Felt impulsy and fan service-y, so I drew a few more screenshot redraws of MD Episode 7 but with @lumineary-arts ‘s Murder Drones Swap AU, since it’s a lot of fun! However, I mainly went along with what we know about her AU so far, tho, so I didn’t include other details like Swap!N and Swap!Cyn’s other parent (who would take canon Nori’s place). I’d leave it to the AU’s creator.
I HIGHLY doubt Nate/Swap!N would tell Z/Swap! Uzi to “die mad”, I feel like he would apologize and genuinely feel guilty for sacrificing himself in front of her after she witnessed T/Swap!Thad do the same thing. Also I honestly loved how the solver symbol turned out! It isn’t perfect, but it sure looks great tbh! Also as some of you might know, backgrounds aren’t my strongest suit 😂
This one was pretty simple, but I am SHOOK at how in-canon this turned out to look. If you zoom out really far, it almost looks like a photo from the actual show! This particular screenshot probably isn’t highly significant in the plot, but I thought that Maid V’s appearance in the episode was an excuse to draw Butler Thad (since V and Thad switch places), who of course is just a mere hallucination produced by the Solver here (unfortunately). Since the artist stated that the solver was Russian-speaking in this AU, I guess that it would imply that Butler Thad in this episode would speak the same language!
Finally (my favorite one so far), the girl bosses ever! I’m kinda proud of how this turned out but HOLY HELL drawing the school bus was hard for me. I kinda got a little lazy and mostly blocked the majority of it with clouds 😂 I originally planned on having Swap!Tessa stand alongside Swap!J and Swap!V with a weapon in hand to reflect on her leaderlike personality, but I decided to put her up on the bus to make her look like the lady in charge. I kinda feel like I made her look a bit too intimidating, but I wanted her to have a “girlboss” expression. Look out, SD-L!
I wish I could draw a few more, but I ran out of ideas 😅 Also reminder: I tried to stay as in canon as possible, so PLEASE don’t hesitate to correct me if I made any mistakes!
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Determined to use her skills to fight inequality, South African computer scientist Raesetje Sefala set to work to build algorithms flagging poverty hotspots - developing datasets she hopes will help target aid, new housing, or clinics.
From crop analysis to medical diagnostics, artificial intelligence (AI) is already used in essential tasks worldwide, but Sefala and a growing number of fellow African developers are pioneering it to tackle their continent's particular challenges.
Local knowledge is vital for designing AI-driven solutions that work, Sefala said.
"If you don't have people with diverse experiences doing the research, it's easy to interpret the data in ways that will marginalise others," the 26-year old said from her home in Johannesburg.
Africa is the world's youngest and fastest-growing continent, and tech experts say young, home-grown AI developers have a vital role to play in designing applications to address local problems.
"For Africa to get out of poverty, it will take innovation and this can be revolutionary, because it's Africans doing things for Africa on their own," said Cina Lawson, Togo's minister of digital economy and transformation.
"We need to use cutting-edge solutions to our problems, because you don't solve problems in 2022 using methods of 20 years ago," Lawson told the Thomson Reuters Foundation in a video interview from the West African country.
Digital rights groups warn about AI's use in surveillance and the risk of discrimination, but Sefala said it can also be used to "serve the people behind the data points". ...
'Delivering Health'
As COVID-19 spread around the world in early 2020, government officials in Togo realized urgent action was needed to support informal workers who account for about 80% of the country's workforce, Lawson said.
"If you decide that everybody stays home, it means that this particular person isn't going to eat that day, it's as simple as that," she said.
In 10 days, the government built a mobile payment platform - called Novissi - to distribute cash to the vulnerable.
The government paired up with Innovations for Poverty Action (IPA) think tank and the University of California, Berkeley, to build a poverty map of Togo using satellite imagery.
Using algorithms with the support of GiveDirectly, a nonprofit that uses AI to distribute cash transfers, the recipients earning less than $1.25 per day and living in the poorest districts were identified for a direct cash transfer.
"We texted them saying if you need financial help, please register," Lawson said, adding that beneficiaries' consent and data privacy had been prioritized.
The entire program reached 920,000 beneficiaries in need.
"Machine learning has the advantage of reaching so many people in a very short time and delivering help when people need it most," said Caroline Teti, a Kenya-based GiveDirectly director.
'Zero Representation'
Aiming to boost discussion about AI in Africa, computer scientists Benjamin Rosman and Ulrich Paquet co-founded the Deep Learning Indaba - a week-long gathering that started in South Africa - together with other colleagues in 2017.
"You used to get to the top AI conferences and there was zero representation from Africa, both in terms of papers and people, so we're all about finding cost effective ways to build a community," Paquet said in a video call.
In 2019, 27 smaller Indabas - called IndabaX - were rolled out across the continent, with some events hosting as many as 300 participants.
One of these offshoots was IndabaX Uganda, where founder Bruno Ssekiwere said participants shared information on using AI for social issues such as improving agriculture and treating malaria.
Another outcome from the South African Indaba was Masakhane - an organization that uses open-source, machine learning to translate African languages not typically found in online programs such as Google Translate.
On their site, the founders speak about the South African philosophy of "Ubuntu" - a term generally meaning "humanity" - as part of their organization's values.
"This philosophy calls for collaboration and participation and community," reads their site, a philosophy that Ssekiwere, Paquet, and Rosman said has now become the driving value for AI research in Africa.
Inclusion
Now that Sefala has built a dataset of South Africa's suburbs and townships, she plans to collaborate with domain experts and communities to refine it, deepen inequality research and improve the algorithms.
"Making datasets easily available opens the door for new mechanisms and techniques for policy-making around desegregation, housing, and access to economic opportunity," she said.
African AI leaders say building more complete datasets will also help tackle biases baked into algorithms.
"Imagine rolling out Novissi in Benin, Burkina Faso, Ghana, Ivory Coast ... then the algorithm will be trained with understanding poverty in West Africa," Lawson said.
"If there are ever ways to fight bias in tech, it's by increasing diverse datasets ... we need to contribute more," she said.
But contributing more will require increased funding for African projects and wider access to computer science education and technology in general, Sefala said.
Despite such obstacles, Lawson said "technology will be Africa's savior".
"Let's use what is cutting edge and apply it straight away or as a continent we will never get out of poverty," she said. "It's really as simple as that."
-via Good Good Good, February 16, 2022
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