Problem
Consider the following mini-case: SOSText (fictionalised name) is a non-profit that offers support via text messages for people who are going through mental health crises. The support is primarily driven by a network of volunteers servicing communities in major cities. For years, the non-profit had been collecting a database of messages exchanged and used the data to triage the incoming calls for help and to create training modules to help train its volunteers to better manage difficult conversations with people in great distress. In a 2020 report, the non-profit (which first launched in 2013) stated that "by implementing data science tools and machine learning from day one, we have created the largest mental health dataset in the world." A report section titled "Data Philosophy" added that they share data to support more innovative research, policy, and community organising. Unlike other large-scale datasets on mental health and crisis, the organisation claimed its data had incredible volume, velocity, and variety. However, the positive impact of SOSText remained constrained as financial reasons limited their ability to scale their offerings to more people in different contexts. To overcome this issue, one of the founders of SOSText decided to launch a for-profit spin-off called SmartAssist.ai. This new service planned to use SOSText data (which it said was anonymised) to gain insights that would be incorporated into building new training modules for people recruited by the new spin-off. SOSText and SmartAssist.ai created a data-sharing agreement that allowed controlled access to data solely to build models for training that would improve mental health more broadly to reach a broader and more diverse population of people in distress. SmartAssist.ai would also share a portion of the profits from that software with SOSText to help sustain the operations of the volunteer-driven organisation. SmartAssist.ai also wants to build predictive tools to help assistors identify people who might be at risk of harming themselves to engage in the proactive intervention. Based on the case above, answer the following questions:
Identify and discuss two ethical concerns presented in the case. Analyse the concerns through the lens of the ethical theories covered in the course. What aspects of the ethical landscape do they highlight?