In this paper, we introduce the Societal Readiness Thinking Tool to aid researchers and innovators in developing research projects with greater responsiveness to societal values, needs, and expectations. The need for societally-focused approaches to research and innovation—complementary to Technology Readiness frameworks—is presented. Insights from responsible research and innovation concepts and practice, organized across critical stages of project-life cycles are discussed with reference to the development of the SR Thinking Tool. The tool is designed to complement not only shortfalls in TR (...) approaches, but also improve upon other efforts to integrate RRI, sustainability, and design thinking in research and innovation cycles. Operationalization and early-stage user tests of the Tool are reported, along with discussion of potential future iterations and applications. (shrink)

The introduction of AI into an organisation is linked to many of its functions, changing not only the technical systems but also the organisation of work and the society around it. Technology is often introduced with efficiency goals in mind, but at the same time, the constantly evolving understanding of sustainable and responsible business raises questions about how to ensure socially sustainable, ethical and responsible development and deployment of AI. The introduction of new, complex technologies, combined with the increasing social (...) complexity of the operating environment, can easily create conflicting demands and dilemmas for organisations. In this paper, we explore the organisational tensions in public and private organisations that are planning to deploy or have already experimented with AI. The aim of the study is to broaden the understanding of AI-related organisational tensions: what issues they cover and how they are described by the practitioners working with AI. The research methodology is a qualitative content analysis of transcribed interviews with AI development experts from 42 Finnish organisations. The results are divided into three categories: (1) tensions related to values, (2) tensions related to AI implementation, and (3) tensions related to AI impacts. A total of 12 pairs of tensions were identified within these categories. We argue that by identifying and understanding AI-related tensions, organisations can learn about the positive and negative social, environmental and economic impacts of AI. This awareness enables organisations to consider impacts in advance, focus attention on key issues and act in a more sustainable way when adopting AI. (shrink)