We had the honor of participating in a special event last week on the theme of digital transformation for non-profits. Joining us at NetHope’s Global Summit in Dublin were speakers from Microsoft, Facebook and AWS.
NetHope is an organization that links the world’s largest nonprofits to its most important technology innovators. It was founded in 2001 and works with over 50 global NGOs in 180 countries to improve connectivity, access to IT services and to leverage data for impact. Our CEO Radha Basu was invited to talk about what digital transformation looks like in practice, sharing learnings from our work labeling and enriching the training datasets that power some of the world’s most advanced algorithms.
Radha started by reminding the audience that AI is powered not by code, but by models built from training datasets, which are themselves constructed by humans. Therefore, the quality and effectiveness of an AI tool is hugely dependent on the quality of the human nuance in the training sets.
This is an important insight when thinking about the future of the workforce in an AI-driven world, a theme with broad implications for the social sector. We see it everyday with our clients: the ‘AI Workforce’ is key to accelerating the digital transformation of businesses. Humans are needed to accomplish the human-judgment tasks that power the next generation of computing services. To stay one step ahead of machines, the workforce of the future will have to be diverse, agile and scalable. From that point of view, AI is not a threat for future generations of workers, but rather an opportunity to create more jobs and digital inclusion.
The second part of the talk was dedicated to sharing examples of organisations using AI ‘for good’ in fields like the environment, medicine or to prevent crime. The MAAP project (Monitoring of the Adean Amazon Project) uses high-resolution satellite imagery to detect illegal deforestation in near real-time. Computer Vision is a technology that teaches computers to ‘see’ by feeding them large volumes of images annotated by humans. This technology is used to build driverless cars, but can also be put to work to increase the precision and speed of satellite imagery analysis, and therefore improve the effectiveness of preservation efforts.
In the field of medicine, computer vision is already used to automate the detection of cancer cells. This is an extremely cost-effective way of democratising access to advanced diagnostics, for example in lower-income areas.
For non-profits looking to harness the power of AI to scale their impact, Radha charted the following roadmap: start first by identifying some of the problems with you can solve with AI, then look at your existing data sets. How can you derive insights and action points from their digitisation and labelling? If needed, accelerate data acquisition from the field. When manually labelling or enriching data, look for a large, diverse workforce: this will ensure that your data is more relevant by bringing in different cultural points of view. Finally, partner with universities or researchers looking for use cases at scale: they can help you define and grow your AI workflow with expert guidance.
You can watch some of the talks from the Summit at this link or learn more about NetHope’s remarkable work here: nethope.org.
September was a busy month for the teams at iMerit, and we are glad to share some news with all of you. The first piece of news is that iMerit has won the Asia finals of the MIT IDE Inclusive Innovation challenge. The award recognizes global companies using technology to drive economic opportunity for workers. We will represent Asia in the global finals in Boston on November 8th, along with three other promising companies selected from 165 applicants from 25 countries in the region.
In this video, you can see Jai Natarajan, VP our Technology and Marketing as he presents iMerit to the judges at the Asian finals in Bangkok.
Mr. Jai Natarajan, Vice-President, iMerit at MIT IDE Inclusive Innovation Challenge Asia 2018 - YouTube
iMerit was also in the news in a special edition of ‘BBC Click’ the popular technology show which was shot in Delhi. In front of an enthusiastic young audience at Bikaner House, our CEO Radha Basu talked about AI, the future of work and how the positive social and economic change iMerit helps create in underprivileged communities. You can watch her interview below or see the full programme at this link.
Ms. Radha Basu, CEO iMerit on BBC Click Live - YouTube
To create an algorithm that learns to ‘see’ a typical road the way humans do, data experts first need to classify and then label the different components of the road: for example, “this is a tree, this is another car, this is the curb of the road”. A process which is natural to the human eye and brain needs to be entirely dissected in order to build the data that feeds the algorithm that powers image recognition for a self-driving car. This is not without challenges, the chief one for data experts being: how do I ‘tell what I see’ in a particular image of a road, in words that are predefined and common to all the data experts working on one data set? And what happens when two autonomous vehicles that are trained on different datasets meet? How do they agree on whose rules to use, the way humans automatically agree on following standard driving rules? Taxonomy is a challenge that is common to all fields in machine learning, yet the issue especially critical in the emerging reality of autonomous driving because of its obvious implications for public safety.
To complicate matters further, taxonomy is only one part of an equation that includes other variables such as time available and the level of accuracy that is required on a project. For example, can we adopt a wider ‘flat’ taxonomy that allows for greater speed in execution, but does not include crucial variations within categories ? In the talk, I took the example of roadside ‘vegetation’ as a class of data that the algorithm would be trained to recognize. However, it could be important for the car to be able to distinguish between ‘grass’ (that it can drive on) and ‘agricultural land’ (that is hazardous to navigate). To be efficient, however, most companies choose to adopt a flat taxonomy that does not allow for subclasses within a category of data. The complexity of the scene itself is another element that influences taxonomy: it is not the same to label the components of an urban scene versus a rural road, or a road at night and a road during the day. The challenge becomes broader when you include non-passenger vehicles, like autonomous farm vehicles or trucks.
Lastly, the taxonomy problem is also compounded by the succession of development cycles: it happens that one labeling effort is focused on creating bounding boxes around “Bicycles” while the next round would need labeling of “Bicyclists”. This conflicting taxonomy often introduces the possibility of biases and errors in the labeling of data.
One possible solution to solving the problem of semantic classification is to take an empirical approach to category-naming. Many of the issues linked to data classification arise from the fact that categories are ‘abstract’ (eg: ‘vegetation’ is a high-level concept. In real life, people are more likely to use words like ‘grass’ or ‘nature’). Before you start your data labeling project, take a survey of the people responsible for annotating the data and agree to use the word that most people have intuitively selected to describe the category. If two words are commonly used by the people in your group, you can already forecast issues with the taxonomy of data on your project.
Several companies are working on self-driving cars at the moment, but there is no unified standard on how to teach these cars to ‘see’. I believe now would be the right time to question the assumptions around the data that powers these vehicles, and work towards creating unified standards for labeling this training data. One way to put it is: “self driving cars are safer when they talk to each other”. What’s more, having a unified standard for road data annotation would free up resources to focus on other challenges such as improving the tools to annotate the data. My final prediction is that a movement towards unification will indeed start to take shape in the near future. This will happen either organically through companies opening their datasets or through regulators enforcing industry-wide rules on data labeling.
You can watch Emanuel’s full talk and learn more about the topic at this link.
Digital data services company iMerit announced downtown New Orleans as the location for its first U.S. delivery center. In this location, employees are supporting innovative companies with needs in Spanish and English Natural Language Processing, Computer Vision, and US-based customer service needs. The founding New Orleans team is fully bilingual Spanish-English and skilled in a variety of data services that help train machine learning algorithms. iMerit eventually plans to create over 100 jobs in this center. This represents a significant investment in digital careers of the future in the Greater New Orleans region.
“New technologies like Natural Language Understanding and Computer Vision, rely heavily on humans to create the nuanced data that fuels the algorithms. We operate where people are eager to develop digital skills and to transform their lives and those of their families. New Orleans has huge potential as a multilingual and multicultural hub with strong local backing for business.” iMerit founder and CEO Radha Basu said.
Global Vice President of iMerit Sales, Jeff Mills, added “We are seeing a surge in demand for US based resources in Defense, Insurance, Health Care, Government and Technology. Simply put, our customer’s data is their advantage. They have always been thrilled with our ability to provide custom skilled teams that bring their data to life, and now customers are excited to be creating jobs here in the US.”
Built on the philosophy that the right training and opportunity can turn anyone into a technology professional, the company seeks to provide opportunities for populations with barriers to employment in order to ensure meaningful careers in the digital economy. These jobs will be focused on accessible data jobs that will provide opportunities for employment to underserved members of the community. iMerit also plans to expand its existing US staff of solutions architects and sales and marketing executives.
“The decision for iMerit to select New Orleans for a key part of their operations is significant on many levels,” said Michael Hecht, President and CEO of Greater New Orleans, Inc. “First, the natural language processing work being done by iMerit is cutting-edge, and will have a significant impact on lives around the globe for decades to come. Further, this represents yet another high tech company investing in Greater New Orleans. Finally, iMerit will not only be creating local jobs, but will do this via employing an underserved portion of our citizenry – another example of ‘inclusive innovation.’”
Alongside Louisiana Economic Development (LED) and the New Orleans Business Alliance, Greater New Orleans, Inc. first engaged with iMerit in late 2017 to share details of the market’s business case, including details about the low cost of doing business in the city, the incredible level of collaboration between education and industry, and the unparalleled level of culture that helps in the recruitment and retention of employees.
LED connected iMerit with LED FastStart’s Louisiana Job Connection, whose innovative matching system the company utilized to identify potential employees whose skills and experiences matched available roles within iMerit. GNO, Inc. also assisted with finding office space for iMerit operations as a test of the market. To date, iMerit has hired and skilled 15 employees in New Orleans and is continuing to scale as demand grows for US-based data and customer services. iMerit has secured a long term space in downtown New Orleans, where they will ramp up to full operational staffing.
“In New Orleans and all across the state, Louisiana is proving to be a fertile location for continued growth of the digital media and software development fields,” said Gov. John Bel Edwards. “In our interconnected world, companies like iMerit are leading the way in ensuring our devices and the services we enjoy can seamlessly hurdle language barriers. We congratulate iMerit on this new investment in New Orleans, and we look forward to their continued success in our state.”
Backed by the Michael and Susan Dell Foundation, Omidyar Network, and Khosla Impact, iMerit was founded as a unique for-profit social enterprise to help build the digital livelihoods of the future while effecting positive social and economic change. iMerit’s global client list includes top online retailers, computer vision startups and innovators in financial services and healthcare. Application areas for the data work done by iMerit include autonomous vehicles, medical research, natural language recognition, e-commerce and financial inclusion. The work done in the delivery centers is supported by US-based sales and marketing executives as well as solution architects. Today, the company employs over 1,300 people globally with over 50% being women and over 80% coming from low income families.
New Orleans Mayor Mitch Landrieu said, “New Orleans is our nation’s most immediate laboratory for innovation and change. And our strategic plan to drive economic growth is seeing major results. The announcement that a global tech firm like iMerit is opening its first U.S. delivery center in our city, bringing with it 100 new jobs, is proof positive that the world is taking notice of our progress and renewed business energy. Our future is bright as we continue to attract major investments in the knowledge based economy. As we celebrate our city’s Tricentennial, we have much to be thankful for and much to look forward to as we continue to build a city for the ages.”
About iMerit iMerit is a technology services company, delivering data and digital services for some of the most innovative companies in machine learning, e-Commerce, financial services and computer vision. It does so while effecting positive social and economic change by training and empowering marginalized men and women. Our workforce of over 1300 people powers transformative technologies such as helping driverless cars understand their environment, advancing cancer cell research, improving crop-yield through the analysis of geo-spatial data and delivering on-demand financial information.
About Greater New Orleans, Inc. GNO, Inc. is the regional economic development organization for Southeast Louisiana. The GNO, Inc. mission is to create jobs and wealth in the Greater New Orleans community. The GNO, Inc. Vision is for the Greater New Orleans region to fulfill its potential as one of the best places in the country to grow a company, and raise a family.
During Women’s History Month, we want to celebrate women we feel fortunate to work with every day who are pursuing big, bold visions to create positive change for millions of children and families in global education. Thank you for being such an inspiration to us and to so many others by making learning more inclusive, equitable, and higher quality.
We are encouraged that in the past year we have witnessed women rallying for their rights and protesting in black gowns against harassment. We watched Wonder Woman become one of the highest grossing superhero movies in history, and #MeToo and #TimesUp grow into social movements. We applauded when women in Saudi Arabia received the right to drive, and when women in hockey fought for and won equal pay.
Omidyar Network invests in the best mission-driven entrepreneurs, and we are proud that more than 40 percent of all the education organizations we support — nonprofit and for profit — have been founded or led by women, well above industry average. If you look at the US-based education companies where we have invested, that number exceeds 50 percent.
By Amy Klement, Partner, Global Education & Isabelle Hau, Investment Partner, US Education