Artificial Intelligence: Data Orchard's position and recommended reading

 

In May 2024, we published our position on Artificial Intelligence (AI) ahead of creating our first organisational AI policy. As the world of AI and its sphere of influence has expanded at speed, we have been continuing to assess what this means for us, our products and services, our clients, and the nonprofit sector as a whole. 18 months on, we feel it’s time to share an update on our thoughts and plans around AI at Data Orchard. 

Our current guiding principles for AI:

  • We experiment with AI using an intentional, problem-first approach. We identify problems that AI tools could help us to solve and assess whether these would be better than our current approach. We align with the view that AI is a normal technology like any other, not a silver bullet that needs to be applied in every situation. We deliberately create time and space for testing and reflection, both individually and as a team, to help us share learning, refine use cases and improve policies. As with learning any new skill or adopting any new tool, we understand that doing our due diligence and developing, testing and implementing AI solutions will take more time in the first instance, not less. 

  • We explore AI in line with our values. We are concerned about how the use of AI could affect the quality and integrity of our outputs, and its potential to contribute towards negative social and environmental impacts that contradict our mission. Like any other tools we use in our work, we aim to make use of AI where it is the best solution for the task at hand and is ethically appropriate. We will always have a human in the loop, and we will be open about where and how we are using AI. We love this quote from digital experience agency Manifesto’s Ethical AI Framework: 

“We will embrace [AI] thoughtfully, with our integrity and human-centred values as our constant guide. We all have a responsibility to use this technology with curiosity and care, questioning, learning and using critical thinking as we adopt these tools.” 

  • We see data maturity as the fundamental basis for innovation. Yes, okay, we know we would say that – but we truly believe that the best position from which to take advantage of any new technology (AI or otherwise) is to start with the basics: ensuring that your data is well structured and managed, your staff are equipped with the skills they need, leadership understand and invest sufficient resources into data, and there is a positive data culture in your organisation. If you’re looking to start your journey to becoming AI-ready, we can help – do get in touch.  

AI and our service offerings 

Our mission remains the same: to enable every nonprofit organisation to use data effectively to achieve their goals. We focus on six key challenges we know are well-evidenced issues in the organisations we serve: 

  • They don’t have good data 

  • Their data isn’t being used in useful and meaningful ways 

  • They don’t have the right data skills or capacity 

  • Their data isn’t being used to support decision making 

  • They can’t evidence their impact 

  • They don’t know how to start getting better with data  

We may use AI to help us to help our clients, and we may also help our clients to use AI to help themselves (or their service users) – but ultimately, we see AI as one of many tools to help us solve these problems. We don’t see lack of use of AI as a problem that is a priority to address in and of itself. However, we do note that unauthorised/ungoverned use of AI by staff in organisations with no guardrails or due diligence is a huge risk.   

Data maturity as a foundation for embracing AI 

One of our key services to help address these challenges is our Data Maturity Assessment Tool, which is based on an underlying evidence-based framework. In the coming year, we will be working on revisions to our framework and tool to incorporate AI and its increasingly prominent role. This will require us to grapple with some difficult questions: What does poor, good and great practice look like in relation to AI? How can organisations best balance managing risk and seizing opportunities in relation to AI? How much resource should be invested in AI development and at what realistic cost?  

We are delighted that many of the earliest users of our Organisational Data Maturity Assessment are pioneering the way in AI. For example: 

  • Prostate Cancer UK completed an Organisation Data Maturity Assessment in 2021 when they were developing their first data strategy. Last year they announced a £1.5M AI and genetics project to focus on early diagnosis. 

  • Neath Port Talbot Council completed an Organisation Data Maturity Assessment in 2023 and engaged their entire leadership team of 80 accountable managers in shaping their data strategy and priorities. Their project with Social Care workers using AI for transcription and note taking is featured as one of 30 Use Cases in the Government’s AI library. 

  • Citizens Advice Scotland were among the participants in our first Data for Leaders courses back in 2023. Since then, they’ve been focusing on building their data team, including supporting a staff member to take on a Graduate Apprenticeship in AI and Data Science. They’ve led some groundbreaking work with AI to identify vulnerable clients in relation to fuel poverty and debt, and built their understanding of data protection and data ethics as part of that work. CAS recently completed an Organisation Data Maturity Assessment and their entire senior leadership team just completed our in-house Data for Leaders course. We’re excited to see their next data strategy unfold. 

We’ll be following up with these, and other organisations we’ve worked with, to understand and share good practice around AI, and shape how we can measure and benchmark this. We also look forward to engaging with our community to help us answer these questions. 

Practical AI resources for nonprofits 

We shared a set of resources with our first position on AI that primarily focused on understanding AI (the ‘what’) – here are some of our favourites that focus more on practicalities (the ‘how’): 

More examples of AI use in nonprofits: 

 
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