2) The Opening

Part 2 of the 12-part series - 'A Grand Machine to Beat Covid-19' - considers the present situation in regards to crowdsourcing, open innovation and the response to the pandemic.

A wide range of OI and crowdsourcing mechanisms are currently in use around the world, with many being actively deployed in the struggle against C-19. This section highlights an eclectic diversity of systems, models and strategies – all of which are destined to be replicated, scaled-up and integrated together, in order to construct the Machine. So, in each case, imagine the approach operating at the maximum possible level and being comprehensively, systematically and synergistically applied across all areas of science, technology and innovation.

Opening Innovation

In January 2020, Chinese scientists openly published the Coronavirus’ genetic code, so researchers around the world could start studying it straight away. This simple example of OI has had profound positive impacts, enabling numerous scientific teams to develop C-19-specific technologies within weeks of the disease being discovered.

Many governments, organisations and websites are opening up new resources, such as information-feeds to release data… and online dashboards to present it. The UK government updates official national statistics daily, whilst a specialist WHO website provides global data, regular situation reports and access to a database of research.

The Coronavirus Tech Handbook is a crowdsourced library of tools, services and resources related to C-19. The initiative is helping to spread best practice regarding pandemic-response and enabling the exchange of dashboards to store and interpret data. The new system was initially crowdfunded and is now evolving rapidly.

Many journals have removed their traditional paywalls, to enable open access to all research articles published on the subject of C-19. Organisations offering such free resources include: the Lancet, SAGE, JSTOR, Springer Nature, Oxford University Press and Cambridge University Press.

canSAR is an integrated knowledgebase bringing together multi-disciplinary research around Cancer. The sophisticated information portal collates all relevant research findings and uses AI systems to help identify potentially useful new pharmaceutical and medical treatments. It is now being utilised to help combat the Coronavirus.

Peeref is an online platform and social network for researchers, providing a forum for scientific discussion and improved connectivity. It can also help to facilitate the academic peer review process.

The COVID Symptom Study App crowdsources useful information on public health, symptom-details and infection data, in order to inform scientists and health workers. The CoronaReport App works in a similar way.

PatientsLikeMe is an online platform that invites people to fight against various diseases, by submitting their detailed personal health data for utilisation by researchers. It currently has a dashboard, highlighting the crowdsourced symptomatic and treatment experiences of people with C-19. Open Humans also facilitates a similar kind of productive data donation.

Some systems utilise the crowd to help analyse data. For example, the Zooniverse project recruits volunteers to scrutinise countless photos of the universe (e.g. ‘what shape is this galaxy?’). ReCAPTCHA systems are used by many websites to test whether a visitor is human or robot. This process can cleverly use the answers provided, to productively analyse visual data (e.g. ‘is there a car in this photo?’)

Amazon’s Mechanical Turk provides a platform where people are paid to complete micro-tasks, many of which involve data input or organisation. The system can also be used to incentivise research participants – for example, crowdsourcing respondents for recent C-19 research into mask-wearing practices.

Inducement Prizes offer financial rewards to inventors who develop solutions to pre-specified problems, historically calling forth innovations such as steam-trains, margarine, food-tinning and transatlantic flight. This interesting report details a large number of prize programmes that have been conducted over the centuries.

The InnoCentive platform is an online innovation marketplace, where prizes are awarded to those who solve specific problems. They have recently been seeking designs for ‘New Technologies to Prevent the Transmission of Coronavirus’ amongst other C19-related innovations.

Where InnoCentive relies on networks of amateur (although, often highly-qualified) ‘solvers’, X-Prize competitions generally focus on incentivising startup companies to invent and commercialise radical new inventions. A couple of their big 21st Century contests centred on green vehicles and space flight. The X-Prize is currently building a Pandemic Alliance and has made a platform to collate and present C19-related challenges from all over the world.

Kaggle specialises in running data contests, with a topical current focus on C19. Kaggle competitions often involve opening up half a dataset and then challenging solvers to make predictions regarding the hidden half (success requiring the development of useful algorithms and technologies). These predictions are instantly tested and if better than the competition, then the innovator goes to the top of the leader-board… with others encouraged to try and leap-frog into pole-position themselves.

Advanced Procurement Commitment (APC) mechanisms can work in a similar way to innovation prizes, with governments or other institutions promising to purchase yet-to-exist innovations according to pre-specified metrics. The Gavi Vaccine Alliance have used APCs to incentivise Ebola vaccines and they’re now applying the strategy to C-19.

Demonstrating a fascinating approach to crowdsourced innovation, Foldit makes it into a game. For example, inviting innovators to design and test ‘protein-binders’ within modelled virtual-environments. The best protein-binder designs are then offered to pharmaceutical researchers, expanding their toolset in the fight against the Coronavirus. The Eterna OpenVaccine project also uses a gamified approach, aiming to encode a novel mRNA vaccine.

Across the world, standard regulations for pharmaceutical development are being adapted to enable greater flexibility and faster innovation timelines (such as allowing new drugs to skip certain stages of testing). For example, the EU have released new guidelines for researchers in the C-19 context.

Hackathons emphasize collaboration, inviting solvers to come together (physically or virtually), for a set period of time, and work intensively on developing a new innovation. There have been numerous Coronavirus-related initiatives, including the COVID-19 Global Hackathon looking for software solutions.

The Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative makes open calls for volunteers, in order to mobilise the UK’s wider scientific community to assist with pandemic modelling.

The Open Source COVID19 Medical Supplies Facebook group is crowdsourcing improved designs for personal protective equipment (PPE). The UK National 3D Printer Society deployed a ‘crowd-production’ strategy to enable printer-owners to help provide PPE for the National Health Service.

Opening for the Machine

There are many more examples that could have been included, but the point is: almost all the component parts of the MMM already exist. The core crowdsourcing, OI, platform-networking, collaboration and digital systems required to build the Machine, have been tried, tested and proven in the real world. All that needs to be done, is to develop new, improved versions of these systems and scale everything up, whilst integrating it all together on a centralised platform.

It’s important to do this, because OI currently lacks:

· Scale (especially in financial terms)

· Integration

OI and crowdsourcing have a long history of success, but have never managed to attract public funding on any serious scale (an inducement prize of $10 million is considered unusually large, despite the fact that major innovation projects often require billions of dollars in investment). It seems as if the world’s policymakers have observed the success of ultra-low-cost/ ultra-high-benefit systems like Wikipedia and concluded: ‘Crowdsourcing seems like a good way of getting things done cheaply’. When really they should be saying: ‘Crowdsourcing seems to get good results for relatively little investment, I wonder what could be achieved if proper money was put into it?’

The other problem is that OI and crowdsourcing projects are mostly run in isolation and rarely connect with one another… or into the broader innovation process. Open data programmes generally don’t incentivise the productive utilisation of the resources they offer. Ideation prizes usually generate ideas that no one will ever work into real-world application. Prototype competitions tend to result in inventions that no one will ever commercialise. The initiatives are not really attached to anything… they’re not integrated into the wider innovation system.

Thus, there is a great opportunity to integrate OI and crowdsourcing mechanisms together, scale everything up, and create a whole that is significantly more than the sum of its constituent parts. A new-style of innovation system – Wide Open Innovation.

Read the next blog in the series - Part 3 - The Knowledge Refinery