Continuing on from Mobile and Cloud First, “AI First” is quickly becoming a top solution strategy for industry and governments, as evidenced by massive artificial intelligence (AI) investments in the billions. IDC has predicted revenues of nearly 50 billion globally in 2020 at a 55% compound annual growth rate. But it’s not just about business growth: AI is potentially one of the most powerful accelerators of the 17 United Nations Sustainable Development Goals (SDGs).
British computer scientist Alan Turing made predictions about machine learning way back in 1947. Fast forward to 2017, when Microsoft CEO Satya Nadella, speaking in India, called AI the ultimate breakthrough technology, which is realized today in intelligent agents, augmented reality, and rapid advancements in deep neural nets providing fundamental human-like perception.
AI, for instance, is currently being used to mine opportunities from the data within India’s 1.1 billion-citizen, biometric digital identity system, Aadhaar. The possibilities were discussed amongst entrepreneurs at the Financial Services Roundtable Fintech Ideas Festival CEO-summit in January.
That’s just one example of the overlapping amplification of value that could come out of this period of unprecedented acceleration of economic, cultural, and societal change driven by what I call ‘A Triple C’:
- time Compression in new innovations;
- Convergence in biological and digital existences;
- ubiquitous Connectivity.
The underlying catalyst of “A Triple C” is a digital AI mesh created by the growing deployment of machine learning — the “AI of Everything”.
AI for global good — Accelerating the SDGs
So how can the power of AI be harnessed for social good? How can it accelerate the SDGs? There are a growing number of use cases for AI enabling the SDGs. Here are a few of them:
|SDG 1: No poverty
AI will provide real-time resource allocation through satellite mapping and data analysis of poverty.
|SDG 2: Zero hunger
Agriculture productivity is increased through predicative analysis from imaging with automated drones and from satellites. Nearly 50% of crops are lost through waste, over consumption and production inefficiencies. Livestock production losses are 78%.
|SDG 3: Good health and well-being
Preventative healthcare programs and diagnostics are significantly improved through AI leading to new scientific breakthroughs. There are 8 billion mobile devices with smartphone cameras being used to diagnose heart, eye and blood disorders; microphone and motion sensors yielding insights into bone density and osteoporosis — and managing cancer, diabetes and chronic illness remote care.
|SDG 4: Quality education
Virtualized, intelligent mentors and responsive personalized learning is revolutionizing education, and improving participation and outcomes — all powered by AI. Online providers such as Coursera have AI-produced granular information for effective learning. Big data analysis is improving graduation rates of low-income and first-generation college students by 30%, spotting warning signs before dropout to allow targeted interventions.
|SDG 5: Gender equality
By identifying and correcting for gender bias, further automating/augmenting tasks, AI is empowering women for growth and new opportunities.
|SDG 6: Clean water and sanitation
The Internet-of-Things (IoT) and sensors feeding into the AI of Everything are predicting sanitation and consumption patterns for improved safe water and sanitation provisioning.
|SDG 7: Affordable and clean energy
Green energy in all its forms is continuously improving for increased output and more efficiency by AI real-time analysis.
|SDG 8: Decent work and economic growth
Despite legitimate concerns about automation replacing jobs, AI augmentation and targeted automation with intelligent devices can improve the work environment, increase productivity, and be a significant driver of economic growth.
|SDG 9: Industry innovation and infrastructure
New hybrid manufacturing incorporating AI, IoT sensors, and 4D printing is reshaping industries, representing the ’A Triple C’, and yielding exponential innovation unprecedented in world history.
|SDG 10: Reduced inequalities
Human augmentation using AI-inspired devices both internally and externally provides super senses and knowledge, enhanced physical capabilities, and corrects disabilities yielding a more equal and inclusive society.
|SDG 11: Sustainable cities and communities
The AI of Everything, the digital AI mesh, fed by the ubiquitous IoT, smart devices, and wearables, is already impacting smart cities and helping to create sustainable communities.
|SDG 12: Responsible consumption and production
AI is yielding optimal consumption and production levels with vertical green farms, eliminating waste, and vastly improving yields and resource efficiency.
|SDG 13: Climate action
Climate change data analysis and climate modeling infused with AI predicts climate-related problems and disasters.
|SDG 14: Life below the water
Pattern recognition can track marine-life migration, population levels, and fishing activities to enhance sustainable marine ecosystems and combat illegal fishing.
|SDG 15: Life on land
Pattern recognition, game theory, and wide applications of computer science can track land-animal migration, population levels, and hunting activities to enhance sustainable land ecosystems and combat illegal poaching.
|SDG 16: Peace, justice, and strong institutions
Thoughtful application of AI can reduce discrimination, corruption, and drive broad access to e-government, personalized, and responsive intelligent services. AI can significantly stay ahead of global cyberthreats, the Cyber Kill Chain, in a manner not possible before.
|SDG 17: Partnerships for goals
Multi-sectoral collaboration is essential for the safe, ethical, and beneficial development of AI. ITU is working with other United Nations agencies, and the XPRIZE Foundation, to organize the “AI for Good Global Summit” in Geneva, Switzerland, from 7 to 9 June. The summit will bring together governments, industry, academia and civil society to explore the responsible development of human-centric AI in solving humanity’s grand challenges, including accelerating the all-important SDGs.
The solvable challenges with AI
As strong as the potential is for good, however, AI also carries with it some significant challenges.
A team of scholars working to protect the planet from existential threats ranked AI No. 1 out of ten biggest threats facing humanity. Ethical challenges were actively debated in an ACM panel discussion on ethics in AI with luminaries Joanna Bryson, Francesca Rossi, Stuart Russell, Michael Wooldridge, Nicholas Mattei, and Rosemary Paradis.
The impact of technology on employment is already a challenge with more than 60% of jobs potentially becoming automated in the near term. China, with its manufacturing base and the need to address higher labour costs, is now the top producer of AI research, and has the highest investment. Microsoft co-founder Bill Gates suggests taxing robots that take jobs.
Liability issues also loom large, with the European Parliament, for instance, calling for new liability rules. “EU-wide rules are needed for the fast-evolving field of robotics, e.g. to enforce ethical standards or establish liability for accidents involving driverless cars,” say MEPs in a resolution voted on 16 February. MEPs request that the European Commission propose rules on robotics and artificial intelligence, in order to fully exploit their economic potential, and to guarantee a standard level of safety and security. Areas of focus included liability rules, the impact of robots on the workforce, a code of ethical conduct and a new European agency for robotics.
Bias inherent in some current iterations of AI can also prove problematic. The Association for Computing Machinery (ACM), the top global computing science organization has recently issued seven principles to foster algorithmic transparency and accountability to avoid bias created by AI. “A few examples of potential algorithmic bias that have been featured in government reports and news articles include: (1) Job hunting web sites: Do these sites send more listings of high paying jobs to men than to women? (2) Credit reporting bureaus: Does the data set that algorithms weigh in determining credit scores contain prejudicial information? (3) Social media sites: What factors go into determining the news items that are served up to users? (4) The criminal justice system: Are computer generated reports that influence sentencing and parole decisions biased against African Americans?”
As with any new revolution, there are growing pains, or challenges. The good news is that they are being openly discussed and addressed, including work on standards. AI developments are unstoppable and the benefits will be mined.
Go in-depth with our special edition of ITU News Magazine.
By: Stephen Ibaraki