Katrin Elsemann is Managing Director of Social Entrepreneurship Netzwerk Deutschland (SEND). In an interview, she discusses the promotion of AI that provides benefits for the common good and what is needed to advance its development.
“Technology is not an end in itself – we want to use it to make a difference.”
Policy Lab: Ms Elsemann, your network wants to lend the social entrepreneurship sector in Germany a voice. What are the characteristics of a good social enterprise?
Elsemann: To join our network, organisations must satisfy different criteria, which we divide into three categories: social and/or ecological goals, business aspects, and corporate governance. The enterprise defines social and/or ecological objectives to make its aspiration to solve a social or ecological problem concrete. Rather than being merely accompaniment, it constitutes the enterprise’s core and the reason why it was established in the first place. The business aspect involves demonstrating a viable business model so that the organisation can continue to survive in the long term. This model should not be completely dependent on volatile grants but, for example, finance itself through the sale of services or membership fees. Many of our members have hybrid sources of income. The all-important corporate governance criterion refers to the need for a sustainable structure within the company. This concerns the way customers or employees are treated or the sustainable use of profits. These are all criteria of a good social enterprise.
Policy Lab: How does the German social entrepreneurship sector compare internationally?
Elsemann: Favourably, albeit to differing extents – better in some areas than in others – but, generally speaking, Germany is lagging behind. This is evident from different studies. In a study conducted by the Thomson Reuters Foundation in 2019, for example, Germany ranked 21st out of a total of 43 countries surveyed. What is missing is an inter-agency strategy in this area. There is scope for improving ecosystems for funding and growth opportunities. However, we also owe this situation to the fact that we have a strong social market economy and an effective welfare system that performs many of the tasks that in other countries it is necessary to organise via social enterprises.
Yet, the current momentum is positive. We’re relatively far ahead in this respect. Companies that are younger than ten years old are generally more likely to be social enterprises. So, we can see that many young companies in Germany are committed to social entrepreneurship.
Policy Lab: What conditions must be met for AI applications to be used by companies for the benefit of the common good? And, against this backdrop, what aspects should the development of AI applications providing benefits for the common good take into account in your view?
Elsemann: Companies should always think in terms of the goals they are pursuing. Technology is not an end in itself; we want to use it to make a difference. For AI companies, the key question is what they want to achieve with the new development. The target group must be involved. So, as I see it, one of the criteria for the development of good applications providing benefits for the common good is to include as many groups and stakeholders as possible. Steps should be taken to ensure that the algorithm is not developed solely from the perspective of researchers or developers but also reflects the target group’s reality.
Policy Lab: At first glance, orientation towards the common good and the pursuit of profit would appear to be mutually exclusive. How can this apparent conflict be resolved?
Elsemann: The orientation towards the common good and the pursuit of profit don’t necessarily have to be mutually exclusive. An enterprise that is committed to providing benefits for the common good needs profits to sustain itself and grow and, in this way, to strengthen the common good. The question is whether we necessarily need to maximise those profits. In my view, attempts to maximise financial gains are always only possible at the expense of the common good.
"Space must be created for people active in the areas of AI and the common good to meet in order to agree on and work towards achieving shared goals. These spaces do not always automatically arise given the 'bubbles' I already mentioned that we sometimes live in. What they need is a forum."
Policy Lab: What underlying political conditions are required to provide effective support for social enterprises and their employees who use AI applications? Does the current situation cover the needs of social enterprises or do you see room for improvement?
Elsemann: There’s definitely a need for adjustment and improvement. We’re fighting for technological progress that primarily addresses societal challenges. Unfortunately, however, social enterprises that want to use artificial intelligence to solve problems are currently having trouble finding investors and raising funding. Social and environmental criteria are not being acknowledged. So, the question is how to make the orientation towards providing benefits for the common good the underlying principle for financial support. There must be a level playing field for enterprises seeking to use AI for solving societal challenges. One aspect of this concerns access to sources of funding.
Policy Lab: SEND is a cooperation partner of the Civic Innovation Platform. What do you think this partnership can offer and what synergistic effects do you expect?
Elsemann: We have learned a lot from the partnership. We all move in “bubbles” and with the Civic Innovation Platform, we can work even more effectively with research institutes, developers, and enterprises in civil society and in the social sector. This creates opportunities for bringing together different perspectives and for working jointly to achieve the greatest possible effect.
Policy Lab: Do AI applications already play a role in your network and, if so, in what areas?
Elsemann: Yes, they’re already playing a role. Not with all organisations as they are highly technological and, for this reason, very expensive in some cases. But they are already in use in some areas. In the ecological area, for example, attempts are being made to develop sustainable algorithms with the aim of making purchasing decisions “greener” or calculating the ecological footprint. Another area is the promotion of democracy, which is using AI-based methods to facilitate citizens’ participation in politics, for example.
Policy Lab: Looking forward, what must be done to strengthen AI and orientation towards providing benefits for the common good?
Space must be created for people active in the areas of AI and the common good to meet in order to agree on and work towards achieving shared goals. These spaces do not always automatically arise given the “bubbles” I already mentioned that we sometimes live in. What they need is a forum. However, we also require a political framework that promotes precisely this. By defining criteria for eligibility, it is possible to make sure that funding is only available for AI developments providing benefits for the common good. It is necessary to create incentives to drive forward the development of AI for the benefit of the common good. Take, for instance, a project that aims to make it easier for the homeless to gain access to support. Developing the right AI application for this would be a good project eligible for funding. In this way, we encourage researchers and developers to operate in the sector devoted to the common good.
Policy Lab: In your capacity as an expert, you witnessed the interim presentation of the award-winning ideas in the first round of the Civic Innovation Platform idea contest. What are the largest challenges now facing the teams in continuing to develop their project ideas?
Elsemann: I was excited by the way people from different companies and organisations came together to form teams. All the groups were highly heterogeneous, and I found this impressive. The greatest challenge is now to retain these complex projects and structures, especially once the initial euphoria has worn off. The longer a project lasts, the more strenuous it can be to stick together and find the resources necessary for the consultation processes.
Policy Lab: The Civic Innovation Platform is a core element of 'Civic Coding – Innovation Network for AI for the Common Good', a joint initiative of the Federal Ministry of Labour and Social Affairs, the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth, and the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection. The purpose of this open network is to pool the three ministries’ resources and to promote and encourage the development and use of AI for the benefit of the common good. What does the social entrepreneurship sector see such a network as needing?
Elsemann: Such a network needs the voice of smaller organisations. The question as to whether research institutes and associations or the people actually working in the social entrepreneurship sector should primarily be involved in the network is crucial. These may be social start-ups, young non-profit initiatives or people doing great work who have so far not had much contact with AI, such as nature conservation organisations. The right groups of people must be brought together in the network and their needs and interests have to be listened to.
Policy Lab: Many thanks for talking to us, Ms Elsemann.