The development and adoption of advanced technologies including smart automation and artificial intelligence has the potential not only to raise productivity and GDP growth but also to improve well-being more broadly, including through healthier life and longevity and more leisure. Alongside such benefits, these technologies also have the potential to reduce disruption and the potentially destabilizing effects on society arising from their adoption. Tech for Good: Smoothing disruption, improving well-being (PDF–1MB) examines the factors that can help society achieve such benefits and makes a first attempt to calculate the impact of technology adoption on welfare growth beyond GDP. Our modeling suggests that good outcomes for the economy overall and for individual well-being come about when technology adoption is focused on innovation-led growth rather than purely on labor reduction and cost savings through automation. This needs to be accompanied by proactive transition management that increases labor market fluidity and equips workers with new skills. Technology for centuries has both excited the human imagination and prompted fears about its effects. Today's technology cycle is no different, provoking a broad spectrum of hopes and fears. Opinion surveys suggest people tend to have a nuanced view of technology but nonetheless worry about the risks: while generally positive about longer-term benefits, especially for health, many are also concerned about the negative impact on their lives, in particular in the areas of job security, material living standards, safety, and trust.
Popular expressions, for example, "artificial intelligence", "machine learning" and "Big Data" have without question become a significant topic in the present tech scene and they are digging in for the long-term. However, the advancement power behind Artificial Intelligence and its related perspectives have additionally discovered its way to the core phase of our society. Can Artificial Intelligence be utilized for the more noteworthy benefit of society? Also, what job should organizations play in it? While AI is certainly not a silver bullet, it can help handle a lot of our general society's most challenging issues on a social, economic and environmental level.
Automation and AI are often perceived by companies that leverage them as an important source of labor productivity. Many workers in such companies, however, tend to see the adoption of these and other technologies as putting their jobs in jeopardy or creating more stressful workplaces. Recent research highlights the dichotomy. While increased robot use contributed approximately 0.4 percentage points to annual labor productivity growth in major developed countries from 1980 to 2014, every additional robot per thousand workers that was deployed in the same period reduced the employment-to-population ratio by about 0.2–0.3 While information and communications technology in the same period and same countries contributed to one-third of total economic growth, technology diffusion in enterprises has contributed in likely the same proportion to increased worker stress.
Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components, including mechanics, sensors and software. AI has made especially large strides in recent years, as machine-learning algorithms have become more sophisticated and made use of huge increases in computing power and of the exponential growth in data available to train them. Spectacular breakthroughs are making headlines, many involving beyond-human capabilities in computer vision, natural language processing, and complex games such as Go. These technologies are already generating value in various products and services, and companies across sectors use them in an array of processes to personalize product recommendations, find anomalies in production, identify fraudulent transactions, and more.