Collaborating Authors


Eden deploys drone technology to help plant one tree at a time


Helping people to help the environment is the core mission at Eden Reforestation Projects, a non-profit that began its work in Ethiopia in 2004, according to the organisation's director of forest monitoring and evaluation Ezra Neale. "A lot of trees are being cut down without any alternatives and local communities are turning towards the land … [and] it creates this endless poverty cycle for the environment and communities; it's all interlinked," he said. "But there's this amazing ability to transform it through planting trees by directly employing and training people to plant trees, totally transforming their lives through a steady income … reinvesting in their community." These days the Los Angeles-based organisation has expanded operations to eight different countries -- Madagascar, Mozambique, Nepal, Haiti, Indonesia, Kenya, and Central America -- and has planted more than 330 million trees. This year alone, the company aims to plant over 120 million trees.

What an all-digital AI research conference looks like


Organizers of the International Conference on Learning Representations (ICLR) shared details about what will be one of the largest-ever all-digital AI research conferences. The weeklong, online-only affair will feature more than 650 machine learning works. ICLR will include live chat, live Zoom video calls for Q&As and research author meetings, and the ability to upvote questions or vote for speakers using Slido. ICLR was initially scheduled to take place next month in Addis Ababa, Ethiopia, but with a global pandemic underway and shelter in place orders asking one in five people worldwide to stay home, the conference will now take place entirely online. ICLR organizers told VentureBeat they're treating the cancellation as an opportunity to develop a model for remote conferences.

Algorithms that run our lives are racist and sexist. Meet the women trying to fix them


Timnit Gebru was wary of being labelled an activist. As a young, black female computer scientist, Gebru – who was born and raised in Addis Ababa, Ethiopia, but now lives in the US – says she'd always been vocal about the lack of women and minorities in the datasets used to train algorithms. She calls them "the undersampled majority", quoting another rising star of the artificial intelligence (AI) world, Joy Buolamwini. But Gebru didn't want her advocacy to affect how she was perceived in her field. "I wanted to be known primarily as a tech researcher. I was very resistant to being pigeonholed as a black woman, doing black woman-y things."

Rediet Abebe


Rediet Abebe uses algorithms and AI to improve access to opportunity for historically marginalized communities. When Abebe moved from her native Ethiopia to the United States to attend Harvard College, she was struck by how vital resources often fail to reach the most vulnerable people, even in the world's wealthiest nation. She now uses computational techniques to mitigate socioeconomic inequalities. While she was an intern at Microsoft, Abebe formulated an AI project that analyzes search queries to shed light on the unmet health information needs of people in Africa. Her study revealed such information as which demographic groups are likely to show interest in natural cures for HIV and which countries' residents are especially concerned about HIV/AIDS stigma and discrimination.

Ethiopia to establish AI research center


The Ethiopian Council of Ministers has decided to establish an artificial intelligence (AI) research and development center. The move was taken "to safeguard Ethiopia's national interests through the development of artificial intelligence services, products and solutions based on research, development and implementation," the Prime Minister's Office said in a statement issued on late Friday. The decision calls for "a conducive environment for beginner developers and startups working in the artificial intelligence sector." This was the latest of a series of measures taken by Ethiopia, Africa's second populous nation with a a population of about 107 million, to step up AI research and development in particular and advance information and Communications technology (ICT) in general. In November, Ethiopia signed a memo with Chinese e-commerce giant Alibaba Group on the creation of an Electronic World Trade Platform (eWTP).

ICLR 2020 Accepted Papers Announced


The International Conference on Learning Representations ICLR 2020 is four months away but has already attracted more than its share of drama with a deluge of submissions and doubts about the qualifications of some reviewers. Yesterday the conference programme chairs finally put the selection process behind them, announcing 687 out of 2594 papers had made it to ICLR 2020 -- a 26.5 percent acceptance rate. ICLR 2020 will be held in Addis Ababa, Ethiopia from April 26 to 30. This will be the first trip to Africa for a major AI conference, a move long-encouraged by many leading AI researchers. All accepted papers will be presented as posters as usual, while 23 percent will have an oral presentation.

Chinese firm to help build artificial intelligence infrastructure in Ethiopia - Xinhua


A Chinese firm has signed a Memorandum of Understanding (MoU) with Ethiopia authorities on establishing a National Artificial Intelligence Infrastructure (NAIF) in Ethiopia, reported state media outlet Ethiopia News Agency (ENA) on Saturday. The MoU was signed between Ethiopia Innovation and Technology State Minister, Sisay Tola and Chen Kuan, the founder and CEO of Chinese firm Infervision Technology Corporation in Ethiopia's capital Addis Ababa on Friday evening, reported ENA. Ethiopia hopes the partnership with Infervision will boost the technological capacity of its education, health care and medical services. Ethiopia also hopes the partnership will facilitate a platform for exchange of ideas and investment opportunities between enterprises of both countries in various sectors including energy, textile, agriculture, construction and information technology. Ethiopia and China have recently signed various agreements in the Information Communication and Technology (ICT), as Ethiopia looks to modernize its largely agrarian economy.

Powered by Artificial Intelligence, smartphones can now ward off banana pests


Banana, a nutritionally-rich, delicious fruit, is a widely-cultivated crop across the world and is a staple diet of people living in parts of Africa, Asia and Latin America. Due to pests and diseases, only 13% of the global production is traded, and often, farmers in India experience severe loss due to fusarium wilt or Panama disease. A novel innovation now aims to change the fortunes of banana growers by helping them detect diseases and pests with their smartphone. In a recent study, researchers from the USA, Democratic Republic of Congo, Uganda, Ethiopia and India have developed a banana pest detection app powered by artificial intelligence (AI). Artificial Intelligence is an emerging arena in computer science where machines are programmed to simulate human intelligence and perform tasks like speech recognition, visual perception, language translation and decision-making.

Dealing With Bias in Artificial Intelligence


Timnit Gebru is a research scientist at Google on the ethical A.I. team and a co-founder of Black in AI, which promotes people of color in the field. Dr. Gebru has been instrumental in moving a major international A.I. conference, the International Conference on Learning Representations, to Ethiopia next year after more than half of the Black in AI speakers could not get visas to Canada for a conference in 2018. She talked about the foundational origins of bias and the larger challenge of changing the scientific culture. Their comments have been edited and condensed. You could mean bias in the sense of racial bias, gender bias.

We are finally getting better at predicting organized conflict


Incidents of conflict and protest, along with many other structural variables, are fed into constituent models. Input variables would include things like population density, GDP growth, travel time to the nearest city, proportion of barren land, years since independence, and type of government. Several different models, each of which uses a different method, compute a probability of conflict. Constituent models could be a conflict history regression model, natural resources model, and an aggregate machine learning model. The results from the constituent models get combined to produce a final risk score.