Many nations have been on a deliberate path to mimic the economic growth path taken by developed countries. These countries have embraced the process of advancing urbanization and shifting the workforce from agriculture to manufacturing to services, with a view toward preparing more of the labor force to participate in higher-value, higher-income activities. Yet technological developments may have created a break in the development chain, rendering that path unpassable by emerging economies. For a continent like Africa, where the population is expected to grow four-fold by 2100, the risk of a burgeoning labor force with no jobs to do is real. To address these challenges and help create societies that are future-fit and more resilient to shocks, governments and their partners in academia, industry, and civil society have launched a wide range of impressive initiatives. In the face of fragility, innovation has emerged as a much-needed driver of stability that can generate public value where traditional approaches have failed to provide solutions.
Trend 1 discussed the importance of algorithmic accountability in the public sector as a means to ensure that AI systems increasingly playing a role in government decision making are transparent and fair. However, what if in addition the public could play a role in elaborating the policies that apply these algorithms in their community? The WeBuildAI participatory framework helps to show governments how such an approach could take shape .
Since 2009, Coca-Cola Freestyle fountains have allowed restaurant customers to mix and match their favourite drinks and flavours. Data collected from these machines over the years showed the company that cherry-flavoured Sprite was very popular, prompting the firm to release it as a standalone brand. When it launched the product, Coca-Cola claimed Sprite was one of the fastest-growing beverages in the US, and that it expects new innovations such as Sprite Cherry to help it continue on this path. This is just a snapshot of the value that data analysis is bringing companies, which we expect to continue.
Forbes has listed the rise of GovTech startups as one of the five biggest tech trends transforming government in 2022, and there are signs of these companies entering the algorithmic accountability space. For instance, Arthur, Fiddler, Truera, Parity and others are actively working with organisations on explainable AI, model monitoring, bias identification and other relevant issues. As the international landscape continues to evolve and solidify, a number of forward-thinking governments worldwide are promoting algorithmic accountability, led largely by oversight and auditing entities, as well policy-making bodies often located at the centre of government.
Moving forward, leaders should focus on the fundamental issue, which is the design and practice of the work itself, as the work will dictate the mix of physical and digital workplace required to meet business outcomes. Unfortunately, only 15% of respondents to the Deloitte 2023 Global Human Capital Trends survey cited the way work is designed as one of the most important attributes in creating the future workplace. Martin is a principal in Deloitte Consulting LLP’s Human Capital Practice, based out of San Francisco. Martin’s focus is on working with clients to help them manage and prepare leaders and employees for large-scale business transformation.
The policy would decrease the burden of proof for victims, establish a “presumption of causality” against the developer, provider or user of the AI system, and make it simpler for victims to obtain information about high-risk systems – as defined by the AI Act – in court. Artificial Intelligence is reshaping economies, promising to generate productivity gains, improve efficiency and lower costs. As governments determine national strategic priorities, public investments and regulations, they hold a unique position in relation to AI. Many have acknowledged the economic importance and potential of AI, with AI strategies and policies now in place in more than 60 countries worldwide.
We don’t know whether the “fourth industrial revolution” in which we are currently engaged is going to look the same as the technological advances that preceded it, but the possibility requires us to learn the lessons of the past. It is not too soon to mobilize—now—to imagine the future of work and design policies and approaches that can optimize its benefits. Recipients of a basic income reported being healthier, happier, less stressed and less depressed than a control group, according to a 2019 report on the first year of the program from Kela, the Social Insurance Institution of Finland.
This involves developing a more holistic Trends Influencing Innovation In The Future Workplace wellbeing approach focusing on mental, physical, and financial wellbeing. The function played a leading role during the pandemic, which has taken its toll. Research by Workvivo reported that a staggering 98% of HR professionals report feeling burned out at some point in the past six months.
RaC could instead see official, machine-consumable versions of these rules produced by governments, concurrently with the natural language versions. This could allow businesses to consume machine consumable versions directly from government, while reducing the need for individual interpretation and translation for some types of rules. Governments and other ecosystems actors have made tremendous progress in this area in just a few years. A spectrum of approaches is unfolding with efforts exhibiting differing levels of maturity. For instance, most standards and principles around the world represent high-level, non-binding recommendations, but concrete laws like the EU’s AI Act and US Algorithmic Accountability Act are coming into focus and have the potential to catalyse and align progress in this area.
https://adprun.net/ and the MBRCGI first explored transparency in the 2017 Global Trends report. Indeed, one of the key focus areas in the recently issued OECD Good Practice Principles for Public Service Design and Delivery in the Digital Age is “be accountable and transparent in the design and delivery of public services to reinforce and strengthen public trust”. Broadly speaking, accountability in AI means that AI actors must ensure that their AI systems are trustworthy. To achieve this, accountable actors need to govern and manage risks throughout their AI systems (OECD, forthcoming-a, Towards accountability in AI).