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Africa: The Hidden Workforce Behind AI

The machines are learning. Slowly, sure, but they are learning and we (humans) are the ones teaching them. We tell the machines how they should learn through the algorithms we write, and then feed them an enormous amount of data, so that it trains endlessly. Data labeling (the process of augmenting unlabelled data with meaningful and informative tags), is a necessary part of machine learning and sadly there’s a simple reason behind the use of a lower-wage workforce to train ML (Machine Learning) models — you only pay them half as much. The market for AI data preparation is projected to leap from $500M in 2018 to $1.2B by 2023.

Data is the only real fodder for any type of AI system. The more it trains on large amounts of ‘good data’, the faster it learns. Behind every piece of machine learning code intended to solve real issues, is a network of digital construction workers bearing the burden of building the foundation for AI — preparing data. For example, AI systems are trained to recognize objects. Data Labelers upload, categorize and cluster millions of images — just about everything from people, animals, buildings, plants, cars, signs, shapes, and things. In doing so, you now have an AI system that can begin to recognize these objects in the real world.

Again, for example, an algorithm meant to classify images of animals uses a large volume of images of different types of animals (dogs, leopards, giraffes, zebras, etc.) to train the model. These images will be labeled and classified for the model to work. A data labeler typically performs this essential function. It annotates the images with the right answers and transforms the dataset into a format suitable for machine/ deep learning.

Data Enrichment for Training ML Models

The real underlying aspect to machine intelligence is ‘the human’ in the AI loop — and it isn’t going away anytime soon either. Functions like data labeling are vital for AI quality control. Big Tech firms readily outsource these tasks to parts of the world where the minimum wage is significantly lower in order to meet extremely ambitious goals within budget. Data preparation and engineering tasks represent over 80% of the time consumed in most AI and machine learning projects. 

For instance, small data labeling companies in Kenya (and others spread across Africa) are working with large American & European firms to help them classify and organize millions of datasets. The task involves highlighting and labeling images of vehicles, traffic lights, landmarks, road signs and pedestrians captured by cameras fixed on autonomous vehicles so that these machines can become aware of the objects around them.

Bounding Boxes (tagging images for machine or deep learning models)

Image Segmentation (recognize objects of different shapes, sizes, and positions)
(source: clickworker)

Automation (the precursor to true AI) has put low-skilled jobs at supposed “extinction-level” risk for several decades now, as self-driving cars, rules-based process bots, and speech recognition will continue to exacerbate this trend. In reality, the advances of digital industrialism are not new, neither is the elimination or replacement of low-skill jobs with newer low-skill jobs. 

Sebenz.ai, a South African AI firm, is trying to create job opportunities for people throughout Africa leveraging the growing demand locally for data labelers. They have produced a Machine Learning ‘labeling game’ that allows people to earn money on their phones by labeling training data for ML models. Using this innovative approach, Sebenz is able to create labeled-data with real-time responses almost in parallel to train these models accurately.

According to the firm, it takes 10,000 hours of audio to train a speech-to-text model. With 1 data labeler, it would take 65 months, but with 10,000 people it would be ready in a few hours. In return, the data labelers are compensated around $16 per day, (minimum wage in the African continent is only a paltry $3 per day), albeit affording them the opportunity to make a better living. Most of the people drawn to data labeling jobs are often unskilled workers and live below the poverty line.

According to a 2018 KPMG research report, 5% or more of the global workforce will be replaced by automation within the next 2 years

When Silicon Valley first began importing ‘cleaned’ data in bulk at nearly a fraction of the price, then it would otherwise cost them in their own markets — it wasn’t initially received as the modest competitive advantage as it is today. However, looking ahead at the ‘future of work’ and the role of Big Tech in shaping the informal economy — the low skilled jobs fueling automation and AI will soon become automated themselves, creating newer jobs and roles for people en masse to move into, yet again.

webinar: AI for data-driven Insurers

Join our Webinar — AI for Data-driven Insurers: Challenges, Opportunities & the Way Forward hosted by our CEO, Parag Sharma as he addresses Insurance business leaders and decision-makers on April 14, 2020.

AI is shaping the future of enterprises and consumer-services in affordable and scalable ways. To learn more about how we can transform your AI journey, reach out to us at hello@mantralabsglobal.com


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MantraTalks Podcast with Parag Sharma: Delivering Digital-first Health Experiences for Patient Care in the New Normal

6 minutes read

The healthcare industry took the brunt of the Covid-19 pandemic from the very beginning. It was, and still is, a humongous task for hospitals to deal with the rising number of COVID patients as well as handling the regular consults. 

To delve deeper into the state of healthcare in the COVID times, we interviewed Parag Sharma, CEO, Mantra Labs Pvt Ltd. Parag shares his insights on how technology can help in delivering digital-first health experiences for patient care in the New Normal.

Parag is a product enthusiast and tinkerer at heart and has been at the forefront of developing innovative products especially in the field of AI. He also holds over ten years of experience working in the services line and has been instrumental in launching several startups in the Internet & Mobile space. His rich domain expertise and innovative leadership have helped Mantra climb to the top 100 innovative InsurTechs in the World – selected by FinTech Global. 

Catch the interview:  

Connect with Parag- LinkedIn

COVID-19 and Its impact on Healthcare Organizations

Considering the COVID situation, according to you how has COVID-19 impacted the IT & service operations among healthcare organizations?

Parag:  Since the onset of COVID-19, the healthcare sector has been deeply impacted. Institutions are facing a serious crunch in manpower. IT support systems which were usually manned and managed by a large team of IT professionals are not available in the same strength. Resource allocation’ is one of the biggest concerns due to physical and mental exhaustion of the healthcare workforce. 

Hospitals are facing issues such as operational disruption due to staff quarantine, supply-chain delays and sudden decline in patient footfalls, difficulty in sustaining fixed costs, etc. People are not comfortable getting out of the safety confinements of their homes due to the rising risk of getting infected with the virus. Hospitals will have to reassess their future strategy and budgets in light of the uncertain economic situation.

Preparing for the Future

What can hospitals do to ensure the continuity of their customer-facing operations in the wake of a second Pandemic wave?

Parag: There are many things that hospitals can do to manage themselves in this hour of crisis. Being more digital than what they are would be one step forward for all of them. They can bring their IT systems to the cloud so that the person can access data and manage their work remotely. They can enable their patients to book appointments and enquire about services through apps and chatbots which won’t require them to call the reception or come to the hospital. These are some of the services which hospitals can provide to their customers with minimum physical contact. 

Related: Manipal Hospital’s move to a self-service healthcare mobile application

Hospitals can extend Telehealth services to their patients. Recently, telehealth has proved to be useful especially when there is asymmetry between the number of patients and healthcare providers. I think it will be very useful for healthcare institutions to deploy telehealth solutions to provide medical facilities to people who have so far been outside the benefits of healthcare.

New Expectations in Health Experiences

Is consumer behavior defined by the ‘new normal’ going to change the way we access healthcare from this point on?

Parag: Yes, people will expect a completely different way to access healthcare services from now on. Hospitals should gear-up and rise to this occasion. The pandemic has also provided a new opportunity to adopt a completely different approach in the way healthcare is delivered. They always felt that medical care cannot be provided remotely but now this is happening and people are appreciating remote healthcare services. Hospitals and healthcare institutions are convinced that telehealth and remote care will be more successful soon.

Technology in Healthcare can Bridge Operational Gaps

What are the operational challenges, as far as digital capabilities go, that hospitals are facing currently? And, what steps must they take to bridge these gaps?

Parag: Operational challenges are not just digital challenges. But a lot of these challenges can be addressed with technology. For example, Electronic Health Records which hospitals manage within the premises can be moved to the cloud so that the person can access these records on the cloud itself and need not come to the hospital. 

Related: Medical Image Management: DICOM Images Sharing Process

Secondly, if you deploy telehealth and telemedicine solutions, irrespective of where your patients are or doctors are, hospitals can deliver the required care to its patients. You can even extend your diagnostics services to your patients by giving them an application through which they can seamlessly book appointments for consults, diagnostics, or pathological services and resolve their queries, etc. Simply by giving a seamless interface either through bots or applications can go a long way in providing better health experiences to the customers.

Role of Chatbots in Superior Customer Experiences

According to you, what role does chatbots powered by Artificial Intelligence have in the Healthcare CX landscape?

Parag: Chatbots are the simplest example of the implementation of AI-based technology in healthcare. There are a lot of things which bots can do simplistically. For example, if a patient wants to book an appointment with the doctors, instead of going through a complex web applications and interfaces, what if I can simply write “I want to book an appointment with the doctor Dr. XYZ at 4 pm” and the bot can figure out in case the time slot is available with that particular doctor, it will confirm the appointment followed by a payment process if the payment has to be made upfront. 

Apart from this, you can extend your bots to provide e-consultations where doctors can do remote consultations via audio and video features of a chatbot. So there is a huge scope for bots beyond answering routine queries by customers or booking appointments. It does not stop just there. You can extend chatbot functionalities to support functions such as admin, HR, finance, and business process efficiency so that they can provide better services to their customers.

Related: Healthcare Chatbots: Innovative, Efficient, and Low-cost Care

Chatbot Use Cases in Healthcare

Could you tell us some possible bot use cases for delivering better customer experiences to digital health users?

Parag: Apart from booking appointments and resolving customer queries, these bots can conduct remote consultations, internal processes, health symptom checker, out-patient video consultation, second opinion consultation, ordering medicines, psychological counseling & mental wellness, scenario-based risk advice, Heroism Recognition for employees, etc. Also, it can be further extended to help patients enquire about health insurance related queries, and all the interactions between insurance companies and hospitals can be provided to the patient. 

Related: Healthcare & Hospitals Use Cases | Digital Health

The Road Ahead

COVID-19 has forced hospitals to revise patient support strategy with limited operational staff that is bringing every day a new challenge. A way out is to heavily rely on digital innovation.

In India we have a disparity between the no. of healthcare providers and care seekers. Without technology, I don’t think there is any way healthcare institutions will be able to scale to a level where they can provide meaningful services to such a large number of people. Hospitals can invest in setting up an information exchange; making the process as seamless as possible; and removing all possible inefficiencies from the supply chain through technology.

Future growth for hospitals will come from digital technology because patients will opt more for digital platforms. And it is up to hospitals to catch up with the pace at which modern technology is developing. We, at Mantra Labs, have achieved several use cases including hospitals/diagnostic centers that are able to deliver superior health experiences.


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