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Home Blog Page 6910

For Smarter Regulation of Airbnb in Africa

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Hotels in South Africa are asking government to regulate Airbnb. They do think – allowing the hospitality platform to operate without regulations will eat into their business opportunities. DStv did ask for the same thing – regulation – against Netflix. Taxi owners did ask for the same element – regulation – against Uber. It is part of the new normal: get the technology portals out so that the old parties could continue!

Major entities in the hospitality industry in South Africa have called for government to step in an regulate Airbnb, according to a City Press report.

Airbnb has seen impressive growth in South Africa, and local hotels are concerned that the unregistered accommodation establishments listed on the platform are taking away business from established bed-and-breakfasts and hotels.

The Federated Hospitality Association of SA (Fedhasa) called for government to crack down on Airbnb, and smaller organisations have echoed this call.

The Port Elizabeth Metro Bed and Breakfast Association (Pembba) added that Airbnb brought in over R6 million in Nelson Mandela Bay last year, 65% up on the previous period.

The fact is that even if government regulates these digital platforms, the trajectory will not change because these platforms operate on near-zero marginal cost where the providers bear all the costs. The man that has a room to rent in Airbnb carries all the costs: no renter, Airbnb loses nothing! Largely, unless you ban it, no hotel can match that pricing because the man can always price lower than hotel chains as its cost model is more competitive. Airbnb will live on anything that comes to it because its cost is close to zero.

So, the shout for regulation will not change anything unless the hotels want to ban Airbnb in the nation. Doing that will be unfortunate since Airbnb provides income-earning opportunities to many citizens of South Africa who have rights to free enterprise as the hotels. By October 2018, South African Airbnb providers had made real money from Airbnb since it launched in the country in 2008. So, this cannot be structured for the hotels to be the sole winners. Others are indeed making money from South African tourism with their properties: “Findings released during Airbnb’s Africa Travel Summit found that South African Airbnb hosts have earned over R4 billion [$290 million] since the platform was founded in 2008, the Sunday Times reports.”

Regulation must be designed to support the South African tax base, leaving markets to decide who wins – hotels or Airbnb providers. So, charge Airbnb hosts the same tax rate you charge hotels and collect all the fees proportionately to track the hotels’. Once you do those, allow market forces to do the job. It is very possible we may not even need hotels in the future, and if that happens, let it be. But do not stunt Airbnb through arbitrary ban. Be fair and let customers decide the winners.

Why Airbnb Struggles In Nigeria

LinkedIn Comment on Feed

The good news about these stuffs (Airbnb, Uber Facebook etc )is that my House, Cars, Phones/laptops etc which could have just been liabilities can be transformed into Assets and bring incomes.
Since what they do solely is to close the gaps between potential services suppliers and services buyers, they play role of income redistribution.

Government area of interest should be on Tax generation and security/safety of the citizen (host and the guest).

Meanwhile Investment of companies in the Hotels, Printing and Logistics businesses needed to be protected because of the fact the established business are real employers of labour. I will suggest that Government therefore put higher Taxes on both Airbnb and the host to save the economy.
Since Airbnb operate at near zero cost, they can always operate at profit. Let them pay higher Tax. The host bears the cost.

The big players are on the receiving ends because of their huge operating costs and admin cost which make their cost high.

The game has already entered Printing business in Nigeria. The software company makes money from the buyer and also charge the printer for using their platform. It is challenging!

Another Comment

The only confusion here is that the Hotels Associations have not told us what exactly needs to be regulated: pricing or business model? It’s a different thing asking the government to save your dying business, in that case – you have the right to do so; but also note that you cannot always get what you ask for.

If we believe in free enterprise, both hotels operators and Airbnb providers are out there to make money, the only thing government should care about, aside from safety is how much comes in as taxes; anything else is more or less a harassment.

Lobbying is fundamental part of political governance, so as Hoteliers lobby the government, the Airbnb providers should also lobby; no one has a superior argument, it’s all about how you see it.

Again, we will always need the big hotels, for various purposes, beyond lodging, you cannot have big conferences or functions in Airbnb provider’s apartment; so the hotels will always be there. Since hoteliers cannot compete in bed and breakfast prices with Airbnb providers; they should reinvent their business model and shift more attention elsewhere.

Alibaba’s Xiang Hu Bao Crowd Insurance Model Could Work in Nigeria

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This is a great idea for health insurance: crowd-insurance. Alibaba Ant Financial’s Xiang Hu Bao, which means mutual protection, has attracted 50 million people since its October inception. Simply, people crowd-insure themselves with no insurance company involved. U.S. Lemonade has something similar but not in health insurance.

The product operates somewhat like a collective, in which members contribute evenly to payouts of as much as 300,000 yuan ($45,000) when a participant falls critically ill. It’s free to sign up, there are no premiums or upfront payments, and disputes about claims are adjudicated by volunteer members, according to a statement from the company on Thursday. In return for managing the process, Ant will take an 8 percent administrative fee out of every payout.

[..]

The company’s foray into health care comes at a time when the country is grappling with a rapidly aging population, one of the more pressing long-term threats to the world’s second-largest economy. Ant said Thursday it hopes to sign up 300 million Xiang Hu Bao users within two years, which would represent more than 20 percent of China’s population.

Managing fraud? “Ant is using the same blockchain technology that underpins digital currencies like Bitcoin, which rely on common verification by members. Members who fall critically ill within 90 days of joining the plan will not be compensated.” They are bringing the tech elements together to deliver new business models.

I think with the deep distrust in the Nigerian insurance, crowd-insurance may be a good idea if the regulators will ever allow such. At least religious organizations and cooperatives can explore the model if platform-tech tools are available to power them. This is a great business to explore in Nigeria but focusing on churches, mosques and cooperatives which already have pre-existing trust infrastructure among themselves.

The insurance industry in Nigeria has used IT for productivity gains. Now is the time for the next level of innovation which is taking the insurance industry to the web. What they have been unable to do for decades – industry penetration acceleration – can happen if they digitize their products and make it possible for Nigerian entrepreneurs to participate via InsureTech. Should that happen, new products will evolve, and could actually deliver the aha moment that will make Nigerians begin to like buying insurance. The time is now: Nigeria needs a 21st century insurance industry.

LinkedIn Comment on Feed

A sort of an insurance model for esusu? Part of the motivation for contribution is that potential date to getting your returns on investment, once that element vanishes, many people could take off… The model can work well for middle-class settings, but what happens to children of the contributors?

Another twist, especially when it’s difficult to know who falls ill more often and who maintains better hygiene. Lots of things to outline. A good experiment worth doing, it can go either way.

Another Comment

Do you realise that that this is very similar to what is already done in the traditional village meetings? Just informally. Where everyone pays levies to the association and when a member is ill or deceased the association handle the cost up to a set amount. As long as the person’s own payment is up to date.

China Plans Dedicated Lanes for Autonomous Vehicles

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These are three trends and technologies which Diamandis has captured.

Dedicated Lanes for AV: According to KPMG, China is currently ranked 20th in the world on its Autonomous Vehicle Readiness Index. To step up its game, the country is developing new road infrastructure with dedicated autonomous lanes. Slated to begin operation in 2020, the first stretch will be a 100 km road connecting Beijing with the Xiongan New Area in Hebei province. The road will embed sensors and electronic tolls that aid in the development of autonomous technology and facilitate easy payment for cab-hailing companies that begin to rely on driverless vehicles.

AI-Authored Book: Scientific journal publisher Springer Nature just released the first machine generated textbook by a scholarly publisher. Developed by the Applied Computational Linguistics (ACoLi) lab at Goethe University in Frankfurt, “Lithium-Ion Batteries: A Machine-Generated Summary of Current Research” is an attempt to distill insights from the vast amount of research in the area. According to Springer, over 53,000 papers on Lithium Ion batteries have been published in just the last three years. While there is an element of human quality control in the training phase, the algorithm condenses and organizes the pre-approved, peer-reviewed publications into coherent chapters and sections, giving researchers just 180 pages to review and consider versus 100,000+.

Road that Recharges EV Buses: Reimagining electric vehicle (EV) charging from the ground up (literally), the Swedish transport administration is now experimenting with electric dynamic charging roads. In a $12.5 million showcasing project, the Smart Road Gotland consortium will pilot a 1-mile stretch of e-road between Sweden’s Gotland Island airport and the town of Visby, capable of charging electric trucks and buses as they run over it. Funded primarily by the Swedish government, the project will leverage a Dynamic Wireless Electrification System developed by Israeli company Electreon, a driving lane-embedded infrastructure that powers vehicle batteries wirelessly.

The Facebook’s Density Map of Africa

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Facebook is working closely with key non-profit and research partners to use artificial intelligence (AI) and big data to address large-scale social, health and infrastructure challenges in sub Saharan Africa. These efforts range from rural electrification in Tanzania to vaccinating people in remote corners of Malawi.

Facebook is applying the processing muscle of its compute power, its extensive data science skills and its expertise in AI and machine learning to create the world’s most detailed and accurate maps of local populations. Facebook also partners with Columbia University’s Center for International Earth Science Information Network (CIESIN (www.CIESIN.org)) to ensure that this effort leverages the best available administrative data for all countries involved.

The Boston-based Facebook team uses advanced computer vision and machine learning to combine satellite imagery from Digital Globe with public census data and other sources to create detailed population density maps of Africa. Using Facebook’s machine learning capabilities, Facebook started developing population density maps to provide better tools to support connectivity efforts around the world. No Facebook data has been or will be used in the project and the census and satellite data used contain no personally identifiable information.

High-resolution satellite imagery already exists for much of the world. However, prior to Facebook’s mapping project, it would have required countless hours for volunteers to comb through millions of square miles of pictures to identify which contained a tiny town or remote village.

The Facebook team used AI to solve that problem, efficiently crunching through data at a petabyte scale. For Africa alone, for example, the computer vision system examined 11.5 billion individual images to determine whether they contained a building. The team found approximately 110 million buildings in just a few days.

“Having started my career at USAID working on malaria control, I have witnessed first-hand the critical role that accurate data plays in the effectiveness of humanitarian efforts,” says Laura McGorman, a public policy manager at Facebook. “What’s exciting about projects like these that they provide an opportunity for our company to contribute to these efforts through our expertise in data and machine learning.”

In Malawi, the Missing Maps Project used these AI-powered maps to filter out the 97% of the terrain that is uninhabited. This helped to coordinate the efforts of 3,000 Red Cross volunteers in Malawi who visited roughly 100,000 houses in just three days to educate people about measles and rubella vaccines

“The maps from Facebook ensure we focus our volunteers’ time and resources on the places they’re most needed, improving the efficacy of our programs,” says Tyler Radford, executive director of the Humanitarian OpenStreetMap Team, which is part of the Missing Maps Project.

In addition to assisting the Red Cross and Missing Maps Project in Malawi, the maps have been used by aid groups like the Bill and Melinda Gates Foundation, the World Bank, and Humanitarian OpenStreetMap. In Tanzania, Facebook’s AI-powered maps helped kick-start efforts to bring renewable electrification to rural areas.

To understand which locations would benefit most from decentralized energy solutions, the Humanitarian OpenStreetMap Team collaborated with the Reiner Lemoine Institut and Integration Environment and Energy to combine Facebook’s population maps with detailed data on settlement locations and structures from OpenStreetMap.

Humanitarian OpenStreetMap team personnel then travelled to villages identified as high priority and conducted surveys to understand the populations’ electricity needs. The results of these surveys were provided to agencies involved in rural electrification, helping mini-grid operators choose the most appropriate locations to begin the work.

The Facebook population density maps project now aims to keep adding new continents and countries.

The Google’s AI with African Accent Arrives

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Google Africa begins the business of AI in Ghana. Below is a press release.


Last year, Google announced plans to open a new AI lab in Africa. Now, Google AI Accra is open for business, and the team there is working on building AI-powered solutions to real-world problems, including helping communities in Africa and beyond to improve their lives.

Google uses Machine Learning (ML) and AI in all of its products and AI and ML are used every day by people across the world, many of who don’t even realise they’re using it. Machine learning is used for everything from filtering out the spam in your email to powering the Google Assistant on your smart speaker, from taking the perfect low-light photos on the Pixel 3 to helping the world speak the same language through Google Translate.

Google recognises that it’s important for everyone that emerging technology is socially beneficial and upholds the highest standards of scientific excellence. Based on its seven guiding principles for ethical use of AI and ML, Google is taking a thoughtful approach to help nurture an emerging technology, which is outlined in depth here.

Google’s AI Centre was opened in Ghana because in order to build technology that benefits people everywhere, it needs to be built by people with a diverse range of backgrounds, experiences and viewpoints. The researchers of Google AI centre in Accra bring a fresh perspective and expertise to build new technologies in Africa that can contribute positively to life here, as well as around the globe.

Google AI Accra forms part of the company’s structured efforts to explore and integrate more diverse experiences / learnings beyond present-day centres of innovation. ‘AI by Africa, for the world’ helps us highlight the crucial role that this new centre will be playing in our vision of using AI to solve problems for everyone, in every part of the world.

A strong focus areas for Google is how AI and ML can be used for social good. We already see how machine learning is improving people’s lives, from protecting us all from spam and fraud to making devices more accessible via speech. Working with partners from such diverse fields as medicine, transportation, environmental  groups and small businesses can help to evolve AI and ML tools to meet real-world challenges. This is why Google shares its machine learning tools, so that organisations outside of Google can benefit.

Google’s AI for Social Good program includes projects such as:

  • Flood prediction: Floods affect up to 250 million people, causing thousands of fatalities and inflicting billions of dollars of economic damage every year. Google has developed a system that combines physics-based modeling with AI to produce earlier and more precise flood warnings.

  • Earthquake aftershocks: existing predictors are little better than chance. So we partnered with Harvard researchers to apply AI to seismic data, and created a model that — while far from fully accurate — can now do a much better job than previous models of predicting where aftershocks will occur.

  • Environmental protection: 6 out of the 13 great whale species are still endangered; even recovering species like humpbacks get entangled in fishing gear and hit by ships. The first step is to know where the whales are. So we’re working with the National Oceanic and Atmospheric Administration — we trained an AI model with over 100,000 hours of underwater audio from 12 different sites in the Pacific, and we can now not only find whale calls, but identify which species is making them.

  • Healthcare and biology:

    • We developed an algorithm to predict heart attacks and strokes simply from images of the retina — no needle or blood draw required!

    • Google researchers have helped doctors detect the spread of breast cancer tumors — the doctors and machine learning system are better working together than either is alone.

  • Environment, agriculture, and natural science:

    • Researchers at Makerere University used TensorFlow to help farmers identify disease in the cassava plant, a major food source in the developing world.

    • A dairy farm in Waynesboro, Georgia is using TensorFlow to keep cows healthier and more productive, similar to the project in the Netherlands

    • Protecting rainforests: Students in Los Angeles schools helped build ‘guardian’ devices that use TensorFlow to listen for chainsaws in rainforests in Brazil.