6) Action Network

Part 6 of the 12-part series - 'A Grand Machine to Beat Covid-19' - details how the networking and project management elements of the Machine facilitate a new type of social and economic organisation.

Social networks (such as Facebook, Twitter or LinkedIn) enable users to link with friends, colleagues, neighbours and peers, join special-interest groups, discuss and debate, communicate and connect. They can facilitate real-world action by spreading messages, summoning people together, and allowing forums for self-organisation.

The Action Network goes further by actively enabling the planning, assignment, tracking, monitoring and management of real-world tasks and actions. Essentially, building project management, emergency management and logistics software systems into the core of the innovation platform.

Challenges and Tasks

MMM activity is structured into interconnected programmes of (Co-operative and Competitive) Challenges. Alongside the Knowledge and Innovation Challenges previously discussed, ‘Social Action Challenges’ focus on helping to organise social support and healthcare response (they are always Co-operative in nature).

For example, the hypothetical ‘Community Support Challenge Programme’ facilitates the systematic arrangement of essential deliveries for shielded or isolated members of local communities. The Programme covers the whole world, breaking down into Challenges on a national level, with every locality and neighbourhood running their own Sub-Challenge. And perhaps a ‘Community Home-Schooling Challenge Programme’ would be useful as well.

The ongoing process of Challenge Definition represents the development of a complete work programme to tackle C-19, covering everything, except the response to the wider economic fallout. Zooming in, these projects divide up into webs of ‘tasks’ and layers of ‘sub-tasks’ – mapping each aspect of the procedure in granular detail… with the cogs undertaking ‘actions’ to complete tasks.

In many cases, the crowd self-assigns tasks voluntarily. Some need to be undertaken by cogs with specific qualifications (e.g. doctors or scientists) and others by individuals with particular roles (selected members of a judging panel, for instance). Sometimes the Machine AI plays an active role in task allocation, such as deciding which bundles of data go to which volunteers for analysis, or suggesting which prototypes are tested in which innovation-evaluation centres.

Some tasks can be tackled independently, whilst others need to be completed in a specific order. Sequence-dependent tasks join together in long chains, with iterative processes mapped in circling feedback loops and alternative pathways branching off after decision and testing points. The workflow is visually represented as a whole, with the capacity to zero-in for details.

Thus, the Grand Challenge of solving C-19 is broken down into dozens of Programmes, hundreds of Challenges, thousands of Sub-Challenges… and millions, or even billions, of tasks and sub-tasks. And so the cogs get to work, progressing through the monumental to-do list, encouraged on through peer-to-peer co-operation and collective monitoring.

Facilitating Challenges

Take the example of Co-operative Knowledge Challenges focused on open data-collation and processing. Volunteers visiting this part of the platform can click on a ‘Collate and Process’ task and the MMM allocates them a bundle of data to feed in and enrich – a bitesize 5-10 minutes of work: inputting, formatting and tagging, etc.

The Machine allocates the same bundle of data to two or three different volunteers (working separately) and if they agree on inputs, the data flows through to the first basin. If not, then it goes back for a repeat review… and if that fails to resolve the discrepancy, then a problem-solving task is generated, calling for the attention of experienced MMM Data Monitors.

The next stages of linking and adding meta-data likewise appear in manageable work-chunks, with similar feedback loops built into the system. And so, a few blocks of tasks (each of a hundred or so individual assignments) manages the whole procedure of feeding a large, newly-released dataset into the MMM. With numerous such projects continuously sourcing information, from all over the world, and the Machine efficiently deploying the crowd to process new datasets, as soon as they become accessible.

In the case of Competitive Ideation Challenges, one of the primary tasks is ‘Submit Entry’ (usually representing a significant investment of effort by the Challenger). Each entered submission generates a dozen or so basic evaluation, filtering and quality control tasks for the cogs. Ideas that go through to the next round generate evaluation tasks that land in the personal to-do lists of specially-selected expert judges. And then the judges have the task of making the final assessment via video-conference discussion.

For Experimental Challenges, Action Network project management also facilitates the submission of physical prototypes to testing centres – generating a range of tasks for the testing team to undertake. Complex programmes of experiments can be project-managed through the MMM, including pharmaceutical Mega-Trials. The networking platform facilitates communication and group problem-solving to keep things moving and avoid bottlenecks along the way.

Community Support Challenges are initiated on a local level, with the first tasks calling for those in need of support to register with the project and for volunteer helpers to sign up. Those requiring deliveries receive tasks asking them to detail their needs. Tasks for volunteers are then generated based on these requirements. Easy communication between all parties is safely facilitated through the MMM. There are various built-in systems – for example, to notify pharmacists regarding who is picking up prescriptions, or to enable financial reimbursement for goods. The Machine interface needs an ‘Accessibility Mode’, so that less tech-savvy individuals can easily access support services.

Facilitating Collaborations

As well as participating in the ongoing process of Challenge Definition, individuals can set up their own ‘Collaborations’ (groups/ teams /projects) on the platform. As with other projects on the MMM, these Collaborations are defined by their primary purpose (for example, ‘Developing a gold-standard diagnostic device’). These projects can be directed towards various diverse ends, with Lego-flexible templates to cover many different types of activity.

Let’s take the hypothetical case of ‘Ash’ – a teacher who just won an Ideation Challenge with his idea for a new distance-learning technology. He now wants to enter the Prototype Challenge, but doesn’t know how to develop software. So he establishes his Collaboration (situated within the ‘Distance-Learning Challenge Programme’) and begins team-building by putting out an open call for assistance. He also sends a personal invite to that techie who made a positive comment during the ideas evaluation stage. The ‘Challenge Winners’ credentials on Ash’s profile really helps to attract talent and he’s able to build a diverse team, including software developers, teachers, and a child-psychologist.

The MMM facilitates a video-conference team-meeting to kick off the project. Ash then maps the tasks and plots the timeline, by tailoring a template ‘Challenger Team’ project plan. Regular team meetings are arranged using integrated calendar-organisation systems. Ash and the teachers are to make a technology-specifications document, the child-psychologist to review, then onto the techies for development… an iterative process with multiple feedback loops built-in. Team-members nudging each other along throughout the project.

Collaborations can also facilitate experiments and clinical trials. Let’s take the hypothetical example of ‘Kim’, who works at a pharmaceutical company and is managing a stage 2 clinical trial to test a new vaccine. She wants to remain outside the Mega-Trial, but use the MMM platform to help facilitate the project. Kim selects the Clinical Trial template project plan (tailoring as appropriate) and invites her colleagues to join the Collaboration. The scale of the Machine makes it easy to recruit 100 trial participants, because at least that many people have volunteered (in advance) to participate in local vaccine trials – so a diverse cohort can efficiently be selected.

Kim sets it up so each participant gets doses of the vaccine on three separate occasions and then gets tested for C-19 every month for the next 12 months. These events show up as tasks, both for the trial-participants and for the staff-team, with the integrated calendar enabling easy scheduling and coordination. The system automatically generates data sheets for the cohort. Various other staff tasks can also be assigned as required, with the template making helpful suggestions as to what might need to be done.

This system scales up to facilitate the treatment and vaccine Mega-Trials, making it easy for different organisations to collaborate on big projects, with everyone able to get a live overview of the workflow. And governments can use the approach to organise major national programmes, as the Machine enables different agencies to efficiently cooperate with one another… and the wider world. On an even grander scale: once the vaccine is (hopefully) discovered, a global vaccination programme could also be orchestrated through the MMM system.

Action Network Features

Platform users are encouraged to provide detailed information on their profiles, in order to enable effective project planning. For example, relevant skills, capabilities and assets should be publicly displayed (Mo has five years of professional care-worker experience, Jules has a car, etc.). A points system rewards participation on the network, with all actions earning varying amounts of credit.

Earning enough points, in a certain way, wins the platform-user a particular type of ‘Medal’ (e.g. Data Processing or Idea Evaluation Medals). Competitive Challenge Winners get Medals and they’re awarded for all manner of useful contributions to the Cause. This system usefully improves information on the platform, whilst simplistically gamifying the experience of the cogs, to encourage further engagement.

Another valuable potential feature could be super-detailed logistical data: a comprehensive map of each ventilator in the area (and on the planet), also test-kits, drugs and everything relevant to the mission at hand. A universal system of resource and logistics data integrating with live manufacturing data could be extremely useful and the MMM platform would be a great place to integrate such technology.

Summary

In summary, the Action Network enables sophisticated collaboration between all sorts of individuals and organisations… working on every kind of complicated endeavour. The simple and intuitive project management system breaks the C-19 Grand Challenge down through multiple layers of scale, into a vast number of person-sized tasks. A comprehensive to-do list for our whole species:

How to beat Covid-19 in ten (billion) simple (and complex) steps!

Read the next blog in the series - Part 7 - Cog Circles