Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI appears to be capable of replacing humans by undertaking intelligent tasks that were once limited to the human mind. However, another school of thought suggests that instead of being a replacement for the human mind, AI can be used for intelligence augmentation (IA). Accordingly, our research seeks to address these different views, their implications, and potential risks in an age of increased artificial awareness. We show that the ultimate goal of humankind is to achieve IA through the exploitation of AI. Moreover, we articulate the urgent need for ethical frameworks that define how AI should be used to trigger the next level of IA.

In March 2017, the United Nations (UN) Statistical Commission adopted a measurement framework for the UN Agenda 2030 for Sustainable Development, comprising of 232 indicators designed to measure the 17 Sustainable Development Goals (SDGs) and their respective 169 targets. The scope of this measurement framework is so ambitious it led Mogens Lykketoft, President of the seventieth session of the UN General Assembly, to describe it as an ‘unprecedented statistical challenge’. Naturally, with a programme of this magnitude, there will be foreseen and unforeseen challenges and consequences. This article outlines some of the key differences between the Millennium Development Goals and the SDGs, before detailing some of the measurement challenges involved in compiling the SDG indicators, and examines some of the unanticipated consequences arising from the mechanisms put in place to measure progress from a broad political economy perspective.

This paper argues that the Global Indicator Framework required to support the 2030 Agenda Sustainable Development Goals will not be successfully populated, using only existing approaches and mechanisms. Official statistical systems must adapt and consider new approaches if only partial success is to be averted. This paper presents a proposal to accredit unofficial statistics as official for the purposes of compiling sustainable development goal indicators. While there may be some reluctance, and there are certainly risks with this proposal, the arguments put forward highlight the potential for collaboration.