AI SPECIAL ....The promise and challenge of the age of artificial intelligence PART III

The promise and challenge of the age of artificial intelligence PART III

5.         AI will also bring both societal benefits and challenges

 Alongside the economic benefits and challenges, AI will impact society in a positive way, as it helps tackle societal challenges ranging from health and nutrition to equality and inclusion. However, it is also creating pitfalls that will need to be addressed, including unintended consequences and misuse.

AI could help tackle some of society’s most pressing challenges

By automating routine or unsafe activities and those prone to human error, AI could allow humans to be more productive and to work and live more safely. One study looking at the United States estimates that replacing human drivers with more accurate autonomous vehicles could save thousands of lives per year by reducing accidents.

AI can also reduce the need for humans to work in unsafe environments such as offshore oil rigs and coal mines. DARPA, for example, is testing small robots that could be deployed in disaster areas to reduce the need for humans to be put in harm’s way. Several AI capabilities are especially relevant. Image classification performed on photos of skin taken via a mobile phone app could evaluate whether moles are cancerous, facilitating early-stage diagnosis for individuals with limited access to dermatologists. Object detection can help visually impaired people navigate and interact with their environment by identifying obstacles such as cars and lamp posts. Natural language processing could be used to track disease outbreaks by monitoring and analyzing text messages in local languages.

Visualizing the uses and potential impact of AI and other analytics

Our work and that of others has highlighted numerous use cases across many domains where AI could be applied for social good. For these AI-enabled interventions to be effectively applied, several barriers must be overcome. These include the usual challenges of data, computing, and talent availability faced by any organization trying to apply AI, as well as more basic challenges of access, infrastructure, and financial resources that are particularly acute in remote or economically challenged places and communities.

AI will need to address societal concerns including unintended consequences, misuse, algorithmic bias, and questions about data privacy

In economic terms, difficult questions will need to be addressed about the widening economic gaps across individuals, firms, sectors, and even countries that might emerge as an unintended consequence of deployment. Other areas of concern include the use and misuse of AI. These range from use in surveillance and military applications to use in social media and politics, and where the impact has social consequences such as in criminal justice systems. We must also consider the potential for users with malicious intent, including in areas of cybersecurity. Multiple research efforts are currently under way to identify best practices and address such issues in academic, nonprofit, and private-sector research.

Some concerns are directly related to the way algorithms and the data used to train them may introduce new biases or perpetuate and institutionalize existing social and procedural biases. For example, facial recognition models trained on a population of faces corresponding to the demographics of artificial intelligence developers may not reflect the broader population.

What AI can and can’t (yet) do

There have been many exciting breakthroughs in AI recently—but significant challenges remain. Partner Michael Chui explains five limitations to AI that must be overcome.

Data privacy and use of personal information are also critical issues to address if AI is to realize its potential. Europe has led the way in this area with the General Data Protection Regulation, which introduced more stringent consent requirements for data collection, gives users the right to be forgotten and the right to object, and strengthens supervision of organizations that gather, control, and process data, with significant fines for failures to comply. Cybersecurity and “deep fakes” that could manipulate election results or perpetrate large-scale fraud are also a concern.

 6.         Three priorities for achieving good outcomes

The potential benefits of AI to business and the economy, and the way the technology addresses some of the societal challenges, should encourage business leaders and policy makers to embrace and adopt AI. At the same time, the potential challenges to adoption, including workforce impacts, and other social concerns cannot be ignored. Key challenges to be addressed include:

The deployment challenge

We have an interest in embracing AI, given its likely contributions to business value, economic growth, and social good, at a time when many economies need to boost productivity. Businesses and countries have a strong incentive to keep up with global leaders such as the United States and China. Increased and broad deployment will require accelerating the progress being made on the technical challenges, as well making sure that all potential users have access to AI and can benefit from it. Among measures that may be needed:

·         Investing in and continuing to advance AI research and innovation in a manner that ensures that the benefits can be shared by all.

·         Expanding available data sets, especially in areas where their use would drive wider benefits for the economy and society.

·         Investing in AI-relevant human capital and infrastructure to broaden the talent base capable of creating and executing AI solutions to keep pace with global AI leaders.

·         Encouraging increased AI literacy among business leaders and policy makers to guide informed decision making.

·         Supporting existing digitization efforts that form the foundation for eventual AI deployment for both organizations and countries.

The future of work challenge

A starting point for addressing the potential disruptive impacts of automation will be to ensure robust economic and productivity growth, which is a prerequisite for job growth and increasing prosperity. Governments will also need to foster business dynamism, since entrepreneurship and more rapid new business formation will not only boost productivity, but also drive job creation. Addressing the issues related to skills, jobs, and wages will require more focused measures. These include:

·         Evolving education systems and learning for a changed workplace by focusing on STEM skills as well as creativity, critical thinking, and lifelong learning.

·         Stepping up private- and public-sector investments in human capital, perhaps aided by incentives and credits analogous to those available for R&D investments.

·         Improving labor market dynamism by supporting better credentialing and matching, as well as enabling diverse forms of work, including the gig economy.

·         Rethinking incomes by considering and experimenting with programs that would provide not only income for work, but also meaning and dignity.

·         Rethinking transition support and safety nets for workers affected, by drawing on best practices from around the world and considering new approaches.

The responsible AI challenge

AI will not live up to its promise if the public loses confidence in it as a result of privacy violations, bias, or malicious use, or if much of the world comes to blame it for exacerbating inequality. Establishing confidence in its abilities to do good, at the same time as addressing misuses, will be critical. Approaches could include:

·         Strengthening consumer, data, and privacy and security protections.

·         Establishing a generally shared framework and set of principles for the beneficial and safe use of AI.

·         Best practice sharing and ongoing innovation to address issues such as safety, bias, and explainability.

·         Striking the right balance between the business and national competitive race to lead in AI to ensure that the benefits of AI are widely available and shared.

By James Manyika and Jacques Bughin https://www.mckinsey.com/featured-insights/artificial-intelligence/the-promise-and-challenge-of-the-age-of-artificial-intelligence?cid=other-eml-alt-mgi-mck-oth-1810&hlkid=d8e6c806ff1747359d88afe9434acd4f&hctky=1627601&hdpid=5e509231-17b4-465a-8942-c2f58b1db936