Where Will AI and the World Be By 2030?

Our world won't be the same in 2030. Artificial intelligence (AI) will further develop smart cities, internet of things, blockchain, healthcare, quantum computing, music, science, and extended reality.

Future superhuman narrow AI applications are here, within us, in our smart networks, devices, processes and services. This includes the following applications: Special-designed automated intelligence outperforms humans in strategic games, chess/go playing, video gaming, self-driving mobility, stock trading, financial transactions, medical diagnosis, NLP, language translation, patterns/object/face recognition, manufacturing processes, etc.

Right now, it's only the narrow artificial intelligence (AI)/ machine learning (ML)/ deep learning (DL) fragmented applications designed for human-like tasks and jobs that are more efficient and effective than human labor. 

The main existential question is when will robots/machines/computers emerge as a general-purpose real-world AI?

Most individuals are still blind to see the disruptive fundamental force of AI technology and its critical impact on our future.

The WEF asked members of its Global Future Councils - academics, business leaders and members of civil society - to imagine a better world in 2030.

Only a few mentioned the role of AI technology for tomorrow’s life, like “by 2030, the combination of space technology and AI will have helped us deal with global challenges like deforestation, oil spills, farming, cross-border terrorism and migration flows”. What if we get things right in 2030? 

Most predictions are in line with the UN 2030 Agenda for Sustainable Development, ignoring the disruptive power of advanced digital technologies, such as AI, ML, DL, Robotics, and other emerging technologies. 

There are several prospective AI world scenarios, positive and negative, utopian and dystopian:

• A global human-machine super-intelligence society interconnected with the intelligent internet of everything.

• A world of humanoid robots. Narrow AI and Robotics could take over the world by 2030, with full domineering of humanoid robots.

• A world of leading China AI. China will lead the world in AI by 2030. By 2030: the world’s leading levels in all AI theories, technologies and applications. By then, China should have become the global centre for AI technologies and Ai economy (value of core AI industries to exceed 1 trillion RMB, while that of AI-related industries to exceed 10 trillion RMB), with a deep and integrated IP application any production segments, social governance, as well as national security and defence, with a series of top-notch AI technology innovation bases and talents leading globally. The Plan for the Development of New Generation Artificial Intelligence (Guo Fa [2017] No. 35). 

• A world of Narrow AI economy. Narrow AI/ML/DL/Robotics will transform the productivity and GDP potential of the global economy. AI contributes up to $15.7 trillion1 to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption-side effects. 

• A world of powerful military AI. Most armies will be humanoid robotic armies with lethal autonomous weapon systems (LAWS) and killer robots. Militaries across the world are already planning on greatly expanding their use of AI and robots on the battlefield by 2030. The head of the UK’s military expects up to thirty thousand “robot soldiers” could form an integral part of the British army in the 2030s.
  
  
• A world without work. By 2030, AI-created technological unemployment without compensation effects will be a major societal concern. Both blue collar jobs, as car or truck drivers, equipment operators, and white collar workers, professionals, lawyers, developers, etc., will see a dramatic shift to AI-enabled intelligence and autonomy and therefore massive job-losses for humans. 

The I-World 2030 scenario would not be possible without the Real-World AI, so the next challenge is about the fragmentation of AI applications and AI reliability and trustworthiness.

To address the issues of narrow AI/ML/DL and robotics fragmentation, we have developed general-purpose, causal AI models, not competing with, but complementing human intelligence.

The general-purpose Human-AI Global Platform is designed to extract knowledge from massive digital data for breakthroughs in all parts of human life, from government to industry to education to healthcare to global security.

This will help to process structured and unstructured digital data within unifying world-intelligence-data models and causal algorithms, shifting from supervised to self-supervised real learning.

Making breakthroughs in these areas will be the matter of life or death for the future of humanity.