4 recommendations for startups that are automating service tasks
Here you can find recommendations for AI and robotics startups that would like to contribute to decent and meaningful work for service employees.
Startups are creating innovative robotics and AI solutions for the service sector that results in a job transformation for the service workforce. It is happening now, it’s not a futuristic discourse or something that will happen when Optimus is working as good as Elon Musk would like it to work. There are robots and AI systems that are currently impacting the service sector. Here are some examples:
Service providers that are early adopters of these technologies might be struggling with some technological or implementation challenges but at some point, the struggles will decrease, and the service industry will adopt them easily. As I tried to explain last time, introducing AI and robotics in the service sector is tricky because, in theory, these technologies will help humans and not displace them, but there’s a very thin line that separates what is sustainable for humans in the long term and what is not.
Then, the question is how can AI startups influence the sustainable development of the service sector? That is, how can they create AI and robotics solutions that are socially responsible and culturally sustainable?
You might think it is not possible to control how automation technology will impact society, and that we cannot do much about it. Research findings show that this is also common thinking within tech startups. The main issues are that tech startups do not feel fully accountable for the deployment of intelligent automation and its impact on society, paired with the fact that they don’t have enough resources to focus on ethical practices. However, even when their responsibility reach appears to be very limited, there are some things they can do to contribute to society’s sustainable development.
Here are the main problems that emerged from our research after talking with 12 AI policymakers, academics, and AI Ethics consultants, and 12 startup members. For each problem we propose some recommendations that fit startups’ limited resources:
ONE
The problem: Some startups don't see the need to worry about AI ethics because their product seems harmless.
When AI and robotics solutions are not compromising the well-being of human beings, e.g. customer service AI chatbots, it seems like no ethical guidelines are needed.
The problem is that AI startup members do not have enough resources to conduct impact assessments to identify how their harmless product may impact society.
Their entrepreneurial methodologies do not encourage formal planning, which prevents the identification of ethical pitfalls.
The recommendation: Do not underestimate your AI and robotics solutions, implement basic impact assessments such as periodic surveys.
Despite how unharmful the AI system may seem; assessments must be done from the early stages of the project and periodically during the implementation to identify all the stakeholders and the implications of the AI system on decent and meaningful jobs.
This basic assessment can look as simple as a feedback survey for service employees or quarterly meetings with service providers to assess the implementation. The aim is to apply such assessments systematically to secure constant monitoring as well as to register and justify all decisions made.
TWO
The problem: Startups may design and develop ethically but service providers implement the technology unethically.
Although AI and robotics startups develop a product with specific features, the way it is implemented does not necessarily promote decent work.
Change management is important to promote decent work in the service sector but it is not planned strategically.
The recommendation: Engage with service providers to design and implement the service experience together.
Startups should be involved in the implementation of AI and robotics technology, not just the design and development of it.
Collaborate with the service providers to improve the task portfolio of service jobs, i.e. promote less physically and mentally demanding tasks; for this, it is necessary to empathize and start a conversation with them, and design the service experience together.
THREE
The problem: Startups sometimes design based on assumptions of what would be best for service employees.
Startups’ members showed a strong opinion on which tasks should be automated: the routinized and mundane. However, service employees may not want their routine and monotonous tasks to be automated.
Only startups’ middle and senior management is empowered to make decisions related to ethics because designers and developers are normally not in touch with clients (service providers).
The recommendation: Work as a multi-stakeholder team and bring the designers and developers into the real service environment.
Promote the immersion of the AI startup team into the real environment of the service provider to have a firsthand experience of how the service is carried out. This could create more empathy and understanding of what the real struggles are, leading to the creation of more meaningful jobs and more successful solutions to real problems.
Support this immersion with design methodologies such as codesign, speculative design or design thinking.
FOUR
The problem: The focus of startups is how to get more investment, not how to act ethically.
AI startup members consider sustainability issues challenging because they often lack tangible results.
Being socially responsible cannot be the main value proposition. Instead, the main advantage of AI and robotics is to have more effective and cheap processes.
The recommendation: Reframe sustainability in the business model to make it attractive to investors.
Find the best way to tackle social impact issues in the business model innovation process by being aware of all the benefits that it brings for the startup’s development; e.g. proposing sustainable solutions is a competitive advantage because both investors and clients could see the ethical standards, policies, and compliance metrics, which would, in turn, help each stakeholder earn trust in a way that competitors cannot.
Consider social impact from the ideation and conceptualization of the key business model elements to be able to demonstrate how social impact can create revenue.
Rojas, A. and Tuomi, A. (2022), "Reimagining the sustainable social development of AI for the service sector: the role of startups", Journal of Ethics, Entrepreneurship and Technology, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEET-03-2022-0005
