The healthcare industry is struggling with a series of challenges, from mountains of unconnected data to caring for an increasingly unhealthy population. While there is huge investment by hospitals, pharmaceutical companies and governments, it is widely acknowledged that the global problem is too big for the industry as a whole.

Harnessing a Global Workforce

The growth of the Internet and global connectivity has created a new opportunity to throw the doors open and invite the world to participate and accelerate research and development. The invitations may be narrow, requiring the invitee to have at least a working knowledge of data science and artificial intelligence, or widely distributed, targeting anyone who has a computer. Some of the challenges offer substantial rewards, others offer smaller, but still worthwhile incentives. Other campaigns offer no rewards, but rely on the goodwill of the person who takes up the challenge to improve the world. Yet, other initiatives use serious games to engage laymen to participate in tasks such as identifying patterns and relaying this information back to scientists working on the bigger picture.

Many of these competitions and challenges require specialized tools, like big data databases and data discovery software. A guerrilla data scientist has shareware and public tools that are available at no cost to himself, except for this time and effort, like R, the preferred software language for data scientists.

There are a surprising number of platforms out there inviting participation, all of which are delivering results and adding value and knowledge at a pace that would not be achievable without public participation. That and findings from the input of the “crowd” is received, assessed and refined in the laboratories and research units of the organizations that put out the original call. Here are some of the notable players in the crowdsourcing arena.

Mapping the Brain; Gamifying Retina Research

The Massachusetts Institute of Technology (MIT) has devised Eyewire, a 3D game to map neurons in the retina. This information is used by researchers at Princeton and MIT, with the help of artificial intelligence and machine learning, to map the behavior of individual cells in the retina. The game players are all apprentice neuroscientists; they are given a 3-D model of a neuron path and asked to predict where the “missing link” is to be found, which they fill in on the game cube. The same patterning is undertaken by others in the game, and the answers are pooled to give an outcome which is then used in the research lab.

Matching Seekers and Solvers: Innocentive

The brainchild of Alpheus Bingham, who worked at Eli Lilly, Innocentive is a platform where requests are made for challenges to be solved by organizations that range from the Mastercard Foundation to the English National Health Services. This marketplace advertises challenges as diverse as optimizing the storage of corrugated cardboard to accurate drug dispensation measurement. All challenges carry some reward, which may range from a few thousand to over a million dollars. Those who load the challenge are known as “seekers”; those who take up the challenge are known as “solvers”, and there are 380,000 of them. Dr. Bingham is a strong believer in open innovation, which he has published a book about, and has opened seven other similar organizations.

Social Investment in Applying Data Science: DrivenData

A similar platform, but less commercial, is DrivenData, which has both “for-good” and financial challenges available for those who want to exercise their predictive muscles. A typical challenge on this site is the prediction of blood donations for a Taiwanese blood bank. They want to know what the likelihood is of any donor donating again when their mobile clinic goes round to the local universities on their next visit. The data for this analysis is provided for the data scientist to perform their predictive analytics. There is no financial reward for the winning answer, but the winner is featured on their website. A similar study, DengAI, is for artificial intelligence to predict the likelihood of Dengue fever outbreaks in Puerto Rico and Peru. There are prizes for some of the challenges, but they tend to be $10,000 or less.

Winning the Data Science Bowl and Fighting Cancer

Kaggle is another company that offers an opportunity to data scientists. While it is a community hub where data scientists can get peer reviews of their work from other members, it also runs competitions, and the 3rd Annual Data Science Bowl has just come to an end. This competition invited participants to help in better lung cancer detection. Over 10,000 data scientists participated in this crowdsourcing initiative, producing 18,000 algorithms to help in the early diagnosis of this prevalent cancer.

Initiatives such as this, not only advance scientific knowledge, they awaken the latent data scientist in people with some mathematical ability, and encourage the growth of the pool of data scientists available by encouraging them to take up this career.