In November last year, Nigeria declared that its water supply, sanitation and hygiene sector was in crisis. This was partly prompted by the fact that the country has struggled to make progress towards ending open defecation.
Almost one in four Nigerians – around 50 million people – defecates in open areas. They do so because access to proper sanitation, like private indoor toilets or outdoor communal toilets, has not improved in recent years.
In fact, it’s got worse: in 2000, 36.5% of Nigerians had access to sanitation facilities that hygienically separate human excreta from human contact. By 2015 the figure had dropped to 32.6%, likely driven by rapid population growth and a lack of sufficient private and public investment.
Open defecation comes with many risks. It can lead to waterborne diseases, cause preventable deaths, and hamper education and economic growth. It also infringes on people’s privacy and dignity.
The government has tried several strategies to address this problem. In 2008 it adopted an intervention called “Community Led Total Sanitation”. This is a community-level intervention aimed at reducing open defecation and improving toilet coverage.
It draws in community leaders and ordinary residents so they can understand the risks associated with open defecation. By 2014 the intervention was deployed in all 36 Nigerian states, covering around 16% of the country’s 123,000 communities.
We wanted to know how effective the programme has been, if at all. So we conducted a study and found that community-led total sanitation programmes alone will not eradicate the practice of open defecation. But they could be part of the solution.
We found that the programme currently works quite well in poor communities but is less effective in richer places – that is, places with higher average ownership rates of assets such as fridges, motorcycles, TVs, smartphones and power generators.
Poorer communities distinguish themselves from richer ones in other ways, too. They tend to have higher levels of trust among their citizens, lower initial levels of toilet coverage and lower wealth inequality. But none of these characteristics is, on its own, as strong a predictor of where the intervention works better than community wealth.
Low community wealth is a simple measure that encompasses all these different features, and is associated with greater programme effectiveness.
Community-led total sanitation typically starts with mobilisation. This initially involves community leaders and then, through them, communities more broadly. Then, a community meeting is held at which residents typically start by marking their household’s location and toilet ownership status on a stylised map on the ground. They also identify and mark regular open defecation sites.
Facilitators use the map to trace the community’s contamination paths of human faeces into water supplies and food. A number of other activities may follow, such as walks through the community that are often referred to as “walks of shame” during which visible faeces are pointed out, to evoke further disgust and shame.
Another common activity involves calculating medical expenses related to illnesses that are caused by open defecation practices.
In 2015 we worked with the charity organisation WaterAid Nigeria and local government agencies in the states of Ekiti and Enugu to design a field experiment in areas with no recent experience of community led total sanitation, or similar interventions.
The community-led total sanitation programme was implemented in a random sample of 125 out of 247 clusters of rural communities.
To study the intervention’s effectiveness, we interviewed 20 randomly selected households before community-led total sanitation took place. We followed up with these households eight, 24 and 32 months after the intervention.
We found that the programme’s roll-out didn’t lead to any changes in sanitation practices in richer communities. But it worked in the poorest communities. The prevalence of open defecation declined by an average of nine percentage points in poorer communities when compared to other poor areas where the programme wasn’t implemented. This drop was accompanied by a similar increase in toilet ownership rates.
Impact depends on wealth
Our results are in line with observations by the designers of the programme. But we are the first to show quantitatively that community asset wealth is a good predictor of whether the intervention can be expected to be successful. Unfortunately, our data does not allow us to pin down why households in poorer communities are more susceptible to the programme. However, these results have important implications for more cost effective targeting of the programme.
Most countries, including Nigeria, have access to readily available datafrom household surveys that can be used to measure how asset-poor a community is. These data can be used to identify and target communities where community-led total sanitation is likely to have the biggest impact.
Eradicating open defecation is not just a Nigerian priority. Today, an estimated 4.5 billion people globally don’t have access to safe sanitation. So we also looked at data and research about this same intervention from other parts of the world.
Community-led total sanitation intervention was first developed in Bangladesh in 1999. It has now been implemented in more than 25 Latin American, Asian and African countries.
We used information from evaluations of this intervention in Mali, India, Tanzania, Bangladesh and Indonesia. The studies found widely differing impacts. These ranged from a 30 percentage point increase in toilet ownership in Mali to no detectable impact on toilet ownership in Bangladesh.
Using a measure of wealth for these countries, we found that sanitation interventions have larger impacts in poorer areas, such as Tanzania, and low or no impact in relatively richer areas, such as Indonesia. This supports the idea that targeting poorer areas maximises the impact of community led total sanitation.
Our research shows that while community-led total sanitation is effective in Nigeria’s poorer areas, there are two main challenges.
First, community-led total sanitation had no perceivable impact in the wealthier half of our sample. There, open defecation remains widespread. And second, even in poor areas, a large number of households still engaged in open defecation after the intervention.
This suggests that while community-led total sanitation can be better targeted, it needs to be complemented with other policies – subsidies, micro-finance or programmes that promote private sector activity in this under-served market.
How Virtual Therapy Apps Are Trying To Disrupt The Mental Health Industry
Millions of Americans deal with mental illness each year, and more than half of them go untreated. As the mental health industry has grown in recent years, so has the number of tech startups offering virtual therapy, which range from online and app-based chatbots to video therapy sessions and messaging.
Still a nascent industry, with most startups in the early seed-stage funding round, these companies say they aim to increase access to qualified mental health care providers and reduce the social stigma that comes with seeking help.
While the efficacy of virtual therapy, compared with traditional in-person therapy, is still being hotly debated, its popularity is undeniable. Its most recognizable pioneers, BetterHelp and TalkSpace, have enrolled nearly 700,000 and more than 1 million users respectively. And investors are taking notice.
Funding for mental health tech startups has boomed in the past few years, jumping from roughly $100 million in 2014 to more than $500 million in 2018, according to Pitchbook. In May of this year, the subscription-based online therapy platform Talkspace raised an additional $50 million, bringing its total funding to just under $110 million since its 2012 inception.
The ubiquity of smartphones, coupled with the lessening of the stigma associated with mental health treatment have played a large role in the growing demand for virtual therapy. Of the various services offered on the Talkspace platform, “clients by far want asynchronous text messaging,” says Neil Leibowitz, the company’s chief medical officer.
Users seem to prefer back-and-forth messaging that isn’t restricted to a narrow window of time over face-to-face interactions. At BetterHelp, founder Alon Matas notes that older users are more likely to go for phone and video therapy sessions, whereas younger users favor text messaging.
“Each generation is getting progressively more mobile-native,” says John Prendergass, an associate director at Ben Franklin Technology Partners’ healthcare investment group, “so I think we’re going to see people become increasingly more accustomed, or predisposed, to a higher level of comfort in seeking care online.”
The ease and convenience of virtual therapy is another draw, particularly for busy people or those who live in rural areas with limited access to therapy and a range of care options.
Alison Darcy, founder and CEO of Woebot, a free automated chatbot that uses artificial intelligence to provide therapeutic services without the direct involvement of humans, says that with Woebot and other similar services, there is no need to schedule appointments weeks in advance and users can receive real-time coaching at the moment they need it, unlike traditional therapy. The sense of anonymity online can also lead to more openness and transparency and attracts people who normally wouldn’t seek therapy.
Along with stigma, the cost of therapy has historically acted as a barrier to accessing quality mental-health care. Health insurance is often unlikely to cover therapy sessions. In most cities, sessions run about $75 to $150 each, and can go as high as $200 or more in places like New York City. Web therapists don’t have to bear the expense of brick-and-mortar offices, filing paperwork or marketing their services, and these savings can be passed on to clients.
BetterHelp offers a $200-a-month membership that includes weekly live sessions with a therapist and unlimited messaging in between, while Talkspace’s cheapest monthly subscription at $260-a-month, offers unlimited text, video and audio messaging.
But virtual therapy, particularly text-based therapy, is not suitable for everyone. Nor is it likely to make traditional therapy obsolete. “Online therapy isn’t good for people who have severe mental and relational health issues, or any kind of psychosis, deep depression or violence,” says Christiana Awosan, a licensed marriage and family therapist.
At her New York and New Jersey offices, she works predominantly with black clients, a population that she says prefers face-to-face meetings. “This community is wary of mental health in general because of structural discrimination,” Awosan says. “They pay attention to nonverbal cues and so they need to first build trust in-person.”
Virtual therapy apps can still be beneficial for people with low-level anxiety, stress or insomnia, and they can also help users become aware of harmful behaviors and obtain a higher sense of well-being.
Sean Luo, a psychiatrist whose consultancy work focuses on machine learning techniques in mental health technology, says: “This why some of these companies are getting very high valuations. There are a lot of commercialization possibilities.” He adds that from a mental health treatment perspective, a virtual therapy app “isn’t going to solve your problems, because people who are truly ill will by definition require a lot more.”
Relying on digital therapy platforms might also provide a false sense of security for users who actually need more serious mental-health care, and many of these apps are ill-equipped to deal with emergencies like suicide, drug overdoses or the medical consequences of psychiatric illness. “The level of intervention simply isn’t strong enough,” says Luo, “and so these aspects still need to be evaluated by a trained professional.
– Ruth Umoh, Diversity and Inclusion Writer, Forbes Staff.
AI 50 Founders Say This Is What People Get Wrong About Artificial Intelligence
Forbes’ new list of promising artificial intelligence companies highlights how the technology is creating real value across industries like transportation, healthcare, HR, insurance and finance.
Naturally, the founders of the honoree companies are excited about the technology’s benefits and, in their roles, spend a lot of time thinking and talking about its strengths and limitations. Here’s what they think people get wrong about artificial intelligence.
Affectiva CEO Rana el Kaliouby says she’s too often encountered the idea that AI is “evil.”
“AI—like any technology in history—is neutral,” she says. “It’s what we do with it that counts, so it’s our responsibility, as an AI ecosystem, to drive it in the right direction.”
Companies need to be aware of how AI could widen bounds of inequality, she adds: “Any AI that is designed to interact with humans—Affectiva’s included—must be evaluated with regards to the ethical and privacy implications of these technologies.”
Sarjoun Skaff, CTO and cofounder of Bossa Nova Robotics, says that the biggest misconception he encounters is that artificial intelligence is actually, well, intelligent.
“The truth is much more mundane,” he says. “AI is a very good pattern-matching tool. To make it work well, though, scientists need to understand the details of how it internally works and not treat it as an ‘intelligent’ black box. At the end of the day, making good use of great pattern matching still belongs to humans.”
Similarly, Aira cofounder Suman Kanuganti says that the public has “over-inflated expectations” for artificial intelligence.
“Garry Kasparov sums it up nicely: ‘We are in the beginning of MS-DOS and people think we are Windows 10,’” Kanuganti says. “AI realistically is still like a 3-year-old child at this stage. When it works, it feels magical. It does some things well, but there’s still a long way to go.”
So, no, we are nowhere close to “artificial general intelligence,” or AGI, where machines are actually as smart as humans.
“We’re still a long way from AI having the general intelligence of even a flea,” says David Gausebeck.
Despite the tendency to overestimate what artificial intelligence can do, the difficulty of building an effective system is often underestimated, some founders say.
“The systems you need to implement and manage machine learning in production are often much more complex than the algorithms themselves,” says Algorithmia CEO Diego Oppenheimer. “You can’t throw models at a complex business problem and expect returned value. You need to build an ecosystem to manage those models and connect their intelligence to your applications.”
Put another way, you can’t just “sprinkle on some artificial intelligence like a magic sauce,” says Feedzai CEO Nuno Sebastiao.
One of the most common tropes that a handful of founders brought up was the idea that artificial intelligence is primarily a job killer.
People.ai founder Oleg Rogynskyy says that AI should be seen as a creator of new opportunities instead of a destroyer of jobs.
“In a nutshell, AI does two things: It automates repetitive low-value-add work for humans (which will indeed take low-complexity jobs away), which we think of as ‘Autopilot,’ and it guides people on how to do their work or other activities better (which makes humans more effective at what they do), which we call ‘Copilot,’” he says. “While Autopilot can take simple, repetitive and boring jobs away, Copilot is absolutely the best way to guide, train and educate humans on how to do new things.”
– By Jillian D’Onfro, Forbes
‘AI Is A Powerful Tool’
Research forecasts that by 2025, machines will perform more current work tasks than humans. Murat Sonmez, member of the managing board, and Head of the Centre for the WEF Fourth Industrial Revolution Network, expands on the role humans might play.
The Fourth Industrial Revolution (4IR) is at the center of the current economic frontier. In reality, is Africa prepared for such changes?
Moving quickly and being agile are key principles of success in the 4IR. Any country can succeed if they take on this mindset. A few years ago, Rwanda saw the opportunities drones, a 4IR technology, brought to their country.
They helped save over 800 lives by delivering blood to remote villages. To scale this, the government worked with the World Economic Forum’s (WEF) drones’ team to create the world’s first agile airspace regulation. Now, we see countries in Africa and around the world looking to the Rwandan model.
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What feasible solutions can artificial intelligence (AI) offer in terms of forecasting natural disasters, droughts food security on the African continent?
AI can help predict diseases, increase agriculture yields and help first responders. It is a powerful tool for governments and businesses, but it needs a lot of data to be effective.
For AI to be all that it can be, countries and companies need to work together to build frameworks for better management and protection of our data and ensure that it is shared and not stored in silos. Data is the oxygen of the (4IR). If countries do not leverage data and have their policies in place, they will be left behind.
There is a growing concern that the 4IR will strip people of jobs, of which there is already a shortage. How true is this?
The world is going through a workplace revolution that will bring a seismic shift in the way humans work alongside machines and algorithms.
Latest research from the WEF forecasts that by 2025, machines will perform more current work tasks than humans, compared to 71% being performed by humans today.
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The rapid evolution of machines and algorithms in the workplace could create 133 million new roles in place of 75 million that will be displaced between now and 2022.
Consumers have real concerns around the potential harm technology can cause in areas such as privacy, misinformation, surveillance, job loss, environmental damage and increased inequality. What ethical precautions are being considered in the robotics space?
Now more than ever, it is important to incorporate ethics into the design, deployment and use of emerging technology. Innovating in the 4IR requires addressing concerns around privacy and data ownership, while attracting the skills and forward-looking thinkers of the future.
There are big challenges and bigger opportunities ahead. We have seen many companies and countries create ethical and human rights-based frameworks. What’s important is they are co-designed with members of both communities along with academia, civil society and start-ups.
A multi-stakeholder approach will result in a more holistic set of guidelines and principles that can be adopted in many different industries and geographies.
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What changes need to take place for the African continent to be on par with global developments, and are there tangible goals set?
The 4IR provides governments the opportunity to be global leaders in shaping the next 20 to 30 years of science and technology. It is important they create an environment where companies can innovate.
The other tenet is to be open to working across borders and learning from each other. The global health industry has access to mountains of data on rare diseases, but it is trapped within countries and sometimes even within the hospital walls.
If we can build trust and find innovative ways to share the data while protecting privacy, we can employ tools like AI to help us cure disease faster. Countries and companies need to have the right governance frameworks and mechanisms in place for these breakthroughs to happen. It is possible to do these things now, but we need to work together to make it happen.
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