4 skills organisations can embrace to use AI for social good

By Pratim Das, Director of Data & AI Architecture and CDO Advisory

07/02/2020

Microsoft has a $165 million commitment to empower those working around the world to solve humanitarian issues, advance global sustainability, and amplify human capability through our AI for Good initiative. The aim of the is to put Microsoft cloud and AI technologies in the hands of those working to address some of society’s biggest challenges around four key programs – AI for earth, AI for accessibility, AI for humanitarian action, and AI for cultural heritage.

Here in the UK, our AI for Good accelerator programme is being run in London by Microsoft and Social Tech Trust. It will support purpose-driven ventures working on solutions to help make a positive impact on the world and our community. The four-month accelerator will give the companies a curriculum jointly designed by Microsoft for Startups, the Social Tech Trust and the Microsoft UK AI team, of which I’m part of.

In 2019 we saw 11 great cohort members graduate, and this year we have welcomed another 12 which we are looking forward to taking through the process.

They’ll get access to workshops and data and AI hacks that will help develop their products and bring them to the market. Also, they will hear from inspiring speakers and take part in Q&As.

When I think about the kind of skills can equip businesses with to develop AI for good capabilities, I wanted to ensure these were relevant across sectors and business sizes. I also want it to be easier for all types of organisations to adopt responsible technology initiatives.

This year there is a focus on execution. We aim for every one of the 12 start-ups to have integrated AI. Moreover, this integration will be done in a very meaningful and responsible way.

“To thrive in their digital transformation, institutions and organisations have to embrace tech intensity. Not only do they have to become fast adopters of best in class technology, at the same time they have to build their own digital capability. I am proud to see the concept of tech intensity come to life through in this year’s AI for Good cohort. From aiming to empower every person to participate in the digital economy through accessibility, supporting humanitarian action and preserving as well as enriching cultural heritage, or solving the some of the world’s biggest health and sustainability challenges; we are proud to support and foster these bold ambitions and make a difference to the world we live in, today.”

Derrick McCourt, General Manager, Customer Success Unit Microsoft UK

1. Get clear on the fundamentals

To help our cohort members infuse their solutions with AI, it’s necessary to build a baseline level of technical knowledge across the group. Our curriculum trace’s official certification paths that are relevant to most of the cohort. These are also available for anyone interested in learning more about AI and its integration with modern AI-infused applications.

Throughout this curriculum, the technical members of the cohort will be able to explore AI solution development with data science services in Azure. They will also publish machine learning experiments with Microsoft Azure Machine Learning services.

The more advanced part of the curriculum is split into two parts:

The fundamentals covering AI foundation, operationalising AI, and responsible AI
Deeper dives on specific use-case with individual cohort members, including hands-on workshops.

By offering a mix of foundational and more advanced modules, the course content stays relevant to both technical and non-technical founders.

2. Move from theory to operational reality

We are seeing AI solutions across all verticals. However, one of the challenges we see when working with organisations of all sizes is their ability to operationalise AI. At Microsoft, we have a mature and battle-tested way of doing this – we call this MLOps, this is built into our machine learning services such as AutomatedML. Customers who prefer to use Python can opt to use our MLOps for Python.

During this process the cohort will learn about AI and infusing it into their applications. They will also have hands-on experiences to operationalise the entire process end to end.

During the foundational part of the curriculum, we will also cover the following courses:

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3. Define what responsible AI looks like to your business

A huge part of our curriculum is the Microsoft Framework for Responsible AI, where they will learn the ethical implications of AI in business. We will share our guidelines to develop a governance model with resources, best practices and tools. As useful as AI is, we must be realistic about the challenges that AI will also raise.

As our President Brad Smith sets out in our eBook The Future Computed; “We don’t believe that we can afford to look at this AI future with uncritical eyes.”

We believe that the development and deployment of AI must be guided by the creation of an ethical framework. Four core principles of fairness, reliability and safety, privacy and security, and inclusiveness. These are underpinned by two foundational principles of transparency and accountability.

Discover how you can be intentional when building AI solutions to focus on the ethical aspects, and how we can build a framework around it:
AI Ethics and beyond talk at Future Decoded

4. Deep dive on specific AI use cases

At Microsoft we believe in tech intensity for our customers and partners, enabling them to “become technology organisations and, in the process, placing themselves at the forefront of technology innovation in their industries,” according to Deb Cupp, Microsoft CVP of Worldwide Enterprise and Commercial.

Getting your hands dirty is the best way to achieve tech intensity. At Microsoft, we run software engineering hacks with developers, DevOps engineers and architects to simplify complex projects are part of our culture – so much so that we have formalised a process of doing this with customers though our OpenHacks on Azure.

From the third workshop onwards, the cohort will be going deeper on their specific use cases. They will ensure their applications are integrated with Azure ML and AI in a meaningful way. By the time they graduate, AI will be infused in their application to drive the right impact.

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We’ll also continue to share what we’re learning in our own AI journey. We recognise that we don’t have all the answers. But, we hope we can provide some useful perspectives though our journey with the AI for Good cohort in our shared mission to make the world a better place for humanity and generations to come.

Find out more

AI for Good Accelerator Programme

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About the author

Pratim Das

Pratim is Head of Solutions Architecture, where he runs a team focused on Data & AI for the Customer Success Unit. Prior to that he was at AWS, as a Specialist SA for Big Data & Analytics, where he advised customers on big data architecture, migration of big data workloads to the cloud, and implementing best practices and guidelines for analytics. Pratim is particularly interested in operational excellence for petabyte to exabyte scale operations, and design patterns covering “good” data architecture including governance, catalogue, and lineage. He’s also passionate about advanced analytics, planet scale NoSQL database like Cosmos DB, and using the right mix of technology, business, and pragmatism to ultimately make customers successful.