Sustainability can be defined as the attribute of a system capable of generating an effect without undermining or detracting from the opportunity to reiterate its generation at the same conditions in the future. But as artificial intelligence begins to pervade in many walks of life, will it support or clash with the aspiration of sustainable development?
Helping our global economy thrive as a system pursuing sustainability in the context of limited resources implies solving a dilemma we come to face early on in life: how is it possible to have one’s cake and eat it? What is the probability of winning the race against time in the replacement of soon to be exhausted resources with viable alternatives? How can far fetching consequences of disruptive innovation be factored in and addressed early enough to secure that negative implications do not outweigh the advantages reaped by turning to new routes and methodologies? Paradoxical aspects may position sustainable development in the domain of utopic aspirations, at least to some extent, but working for sustainability remains a necessary practice. While a growing population is set to leverage the wealth created by the world’s economy and of our planet’s resources, individuals included in today’s digital society claim the right to a greater slice of the pie and collectively aspire to universal democratization of lifestyle standards promoted through global communication channels.
Looking at the future
From a pragmatic standpoint, the pursuit of sustainability implies, among other things, the ability to effectively imagine the future, picturing prospective scenarios and calculating the probability of influence deriving from critical variables. In the context of sustainable development, this exercise of looking ahead to forecast what will or may happen over a longer period of time is fundamental, whatever the system and the purpose it is designed for. It equally applies when managing natural resources, governing societal prosperity and planning for the wellbeing of a community and its individuals, from a collective or subjective standpoint. It implies finding answers to a large number of specific forward-thinking questions, for example:
1. What are the chances that the availability of a given resource such as rare metals, carbon-based fuels or sweet water is exhausted over time, in relation to which factors? What alternatives can be exploited to slow down the consumption of a diminishing resource or to make it totally replaceable system-wide? What geo-political scenario will potentially add or subtract from the necessity to accelerate change? What is the factual contribution to be expected in relation to newly introduced alternatives – and by when, and to what extent is the true outlook just industrial propaganda?
2. At what speed will the effects of one-child only policies decelerate demographic explosion in emerging countries? Conversely, at which extent and pace can they affect accuracy of census and lead to breeding an undercover generation of paperless citizens? At what extent and pace can the imbalanced gender distribution resulting from parental disposing of female offspring determine a sensible influence on the mix in sexual orientation of a population, once its male element becomes severely preponderant?
3. How fast will improvements in Internet connectivity support education programs in communities still slowed down by the digital divide? Which hindering effects will hold back the enrolment and attendance of female students in online courses delivered for homeschooling?
4. How much money can students borrow and invest for their education without burdening their personal credit line to such an extent that it will hinder access to a mortgage or even crush their individual financial outlook once graduation leads to the most probable job offering they can aspire to as next step in their career? What influence on their personal outlook has the probability of their country exiting the Eurozone while they still attend university?
When aspiring to plan for sustainable development in our global, hyper-connected society, exercising a smart, forward-thinking capability is essential. In the era of big data, this ability is to be empowered, well beyond a generic change of gears to the digital and computer-aided level we have been familiar with for decades. A new horizon of prerequisites to be met includes, in fact, the capability of predicting the effects of behavior, the intelligence to undertake complex modeling efforts and draft scenarios, with the possibility of factoring in influence of any new significant variable that may arise. Turning to artificial intelligence is a natural move. It is the complexity of the world we live in and the speed of technological evolution that commands it.
Only with a modern approach in terms of methodologies and technologies it becomes possible to draft the hypothetical prospective scenarios we strive to address as we pursue sustainable development. Imagining the future acquires a whole new dimension as a machine-assisted ability. To generate defendable and actionable plans, a modern vision needs to remain rooted in a fact-based approach and a scientific methodology. If we achieve to excel in this forward-thinking ability by developing the means to speculate in a scientific, fast and adaptive way, the chances of increasing sustainability of any system could already be improved.
When machines take over
There is also a broader subject area we should keep in mind. It is being said that machines will substitute human labor by and large. Will this change the essence of sustainability in a machine-driven economy? How should we picture sustainable development within a society where human labor will have much lesser relevance and to a large effect replaceable value? Which new formulas will be needed to generate and distribute wealth and profits. Will this further weaken today’s ties between labor and profit, work and remuneration? Will this correlation be (or need to be) replaced with alternative formulas of our society’s overall wealth management? This latter aspect of how artificial intelligence transforms our society and our aspirations to sustainable development is most fascinating and it is interesting to examine how governments and international bodies working in both arenas are endeavoring to find common ground
AI appeal from a government’s standpoint
Artificial intelligence is a strategic growth area that should be focused on when thinking of a comprehensive strategy for societal development from a government perspective. An interesting result of growing the AI sector is that it helps individual countries to create jobs for extremely qualified professionals. It implies developing and mastering a series of technologies that are applicable in additional strategic fields. Thus, having a market sector such as ecommerce drive its utilization allows a government to grow and cultivate competencies, experiences, solutions and technologies within their country. No government will be willing to share these with third parties once their effectiveness is proven in highly sensitive fields of application.
In the UK, a Parliamentary Science and Technology Committee recently reviewed advances in robotics and AI and its potential to fundamentally reshape the way we live and work. But it held that the Government does not yet have a strategy for developing the new skills citizens will need to flourish in a world where artificial intelligence is more prevalent, or responding to the social and ethical dilemmas it poses. The committee concluded that artificial intelligence has some way to go before the world sees systems and robots as portrayed in the creative arts such as Star Wars. At present, ‘AI machines’ have narrow and specific roles, such as in voice-recognition or playing the board game ‘Go’. But science fiction is slowly becoming science fact, and robotics and AI look destined to play an increasing role in people’s lives over the coming decades. But is the resulting view that it is too soon to set down sector-wide regulations for this nascent field a blinkered one? This is apart from the recognition that it is vital that careful scrutiny of the ethical, legal and societal ramifications of artificially intelligent systems begins now.
Transformational impacts
AI systems are starting to have transformational impacts on everyday life: from driverless cars and supercomputers that can assist doctors with medical diagnoses, to intelligent tutoring systems that can tailor lessons to meet a student’s individual cognitive needs. Such breakthroughs raise a host of questions for society, including ethical issues about the transparency of AI decision-making as well as privacy and safety. The Committee is calling for a Commission on Artificial Intelligence to be established and believes the UK is well-placed to provide this type of intellectual leadership.
Much of the significant progress in this field—such as improved automated voice recognition software, predictive text keyboards on smart phones and autonomous vehicles—has been driven by UK-based technology start-ups, but, the committee’s view remains that Government leadership in AI is lacking. Similarly, improvements in productivity and efficiency, driven by robotics and AI, are widely predicted. Yet there are conflicting views about what this would mean for jobs in the UK. Some expect rising unemployment as labor is substituted for AI-enabled machines. Others foresee a transformation in the types of employment available, with the creation of new jobs compensating for those lost and AI augmenting existing roles, enabling humans to achieve more than they could on their own.
This opinion is being mirrored somewhat in the US with a recent White House statement that: “AI-driven automation will continue to create wealth and expand the American economy in the coming years, but, while many will benefit, that growth will not be costless and will be accompanied by changes in the skills that workers need to succeed in the economy, and structural changes in the economy. Aggressive policy action will be needed to help Americans who are disadvantaged by these changes and to ensure that the enormous benefits of AI and automation are developed by and available to all.”
Global techno giants step forward
Some major technology companies — including Google and Amazon — have recently come together to form the ‘Partnership on AI’. Is now the time to identify principles for governing the development and application of AI, and to foster public debate. iGiant, Apple has also come out of the woodwork with a report on Simulated and Unsupervised (S+U) Learning, focusing on AI in the world of graphics. With recent progress in graphics, according to Apple, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations. However, learning from synthetic images may not achieve the desired performance due to a gap between synthetic and real image distributions. To reduce this gap, the company proposes simulated and unsupervised (S+U) learning, where the task is to learn a model to improve the realism of a simulator’s output using unlabeled real data, while preserving the annotation information from the simulator. This sees the development of a method for S+U learning that uses an adversarial network similar to Generative Adversarial Networks (GANs), but with synthetic images as inputs instead of random vectors. Several key modifications are made to the standard GAN algorithm to preserve annotations, avoid artifacts and stabilize training: (i) a ‘self-regularization’ term, (ii) a local adversarial loss, and (iii) updating the discriminator using a history of refined images. This enables generation of highly realistic images, showing a significant improvement over using synthetic images, and achieve state-of-the-art results on the MPIIGaze dataset without any labeled real data.
Sustainable strategies
In other quarters, Earth 2017 is looking into reports on the growth of the world’s megacities and the impact AI can have, using Beijing in China as an example. Beijing has 20 million people living in its metropolitan area. A typical driving commute is 5 hours. They have one highway with 50 lanes. This 50 lane highway experienced a traffic jam that lasted for 12 days. Research confirms how mega-cities and urbanization are reshaping the 21st century. There are 25 mega-cities today with populations of at least 10 million people and 20 of these 25 mega-cities are located in developing countries. Additionally, over the next few decades, the number of mega-cities is expected to double to 50 cities. What these mega-cities have in common is unsustainable levels of pollution, landfill waste and congestion. Their success will choke on this lack of sustainability. Recognizing this as opportunity, companies from Ford to Uber to Google are driving an urban technology revolution.
AI, clean tech and IoT
According to Earth 2017, car manufacturer, Ford, has a new vision for our future in cities. It is based on mobility, connectivity and artificial intelligence. Ford is not alone. Uber, Lyft, GM, Apple and Google are all focused on commercializing urban focused technologies that use less energy, use more renewable energy, are cleaner and reduce congestion. The breakout solutions being pursued by these companies are focused on two key technologies – autonomous vehicles – and electrification. The breakout solution is to use Artificial Intelligence (AI) and the Internet of Things (IoT) to create driverless autonomous machines. Autonomous vehicles are projected to cost about a third less to operate than human driven vehicles. Ford estimates that autonomous vehicles can cost $2 per vehicle mile less to operate by removing the driver and from increased operating efficiency. Reducing fuel consumption will also reduce vehicle emissions. This holds the potential of saving more money as governments increasing explore taxing vehicle air emissions.
Additionally, electric vehicles eliminate tailpipe emissions. This is huge for mega-cities choking on pollution. Electric vehicles’ zero emissions will improve quality of life and lower health care costs. Unlike lower emissions natural gas or hydrogen vehicles, an electric car has the potential to be fueled with zero emissions renewable energy. Today, recharging an electric car with utility supplied electricity is at a 75 cents per gallon gasoline equivalent. This cost advantage will grow as wind and solar achieve even lower prices from a global manufacturing economies of scale plus technology innovation. Electric vehicles are on a path of costing less to operate plus delivering zero emissions. Earth’s report states cities are increasingly being defined by congestion and pollution. Building more roads no longer relieves congestion. Mandating increased fossil fueled vehicle air pollution controls is still effective. Technologies that can solve problems tied to pollution, congestion and cost are now the path to urban economic growth. This is a smart and clean technology wave focused on delivering less cost congestion and less pollution.
One major implementation path anticipated is in city buildings. AI, batteries, IoT and renewable energy will combine to create Net Zero Energy buildings that cost less to operate, increase human productivity and have reduced emissions. Sustainability, clean tech and smart tech are emerging as the 21st century’s urban economic drivers. The question for every city, large or small, is how will they harvest this opportunity? According to Earth, the cities that answer that question successfully will win competitive advantage. They will realize more jobs, better jobs and healthier citizens. Their businesses will be able to compete on the global stage.
Communications
The United Nations specialized agency for information and communication technologies, the ITU, is also assessing the compatibility between AI and sustainable development. This organization too poses the question whether AI is a ‘friendly companion or threatening conqueror’. With recent advances in artificial intelligence (AI), machines are gaining the ability to learn, improve and make calculated decisions in ways that will not only enable them to perform tasks previously thought to rely on human experience and ingenuity, as well as to solve problems involving a large amount of data and lots of variables too complex for humans to perceive. Adding knowledge and reasoning to existing applications, AI technology is creating enormous opportunities for beneficial influences on society, such as improving human decision-making capabilities in regard to uncertainty and other complexities.
Existing AI applications offer invaluable assistance to medical research by analyzing huge volumes of medical images – comparing them at a level of detail beyond human capacity, and making connections between structured as well as unstructured data – to identify patterns or correlations in need of further research. So generally, is this the lucky moment for AI? It can perhaps be summed up practically when looking at how volumes of data are made available today both by people and by objects/sensors; or that the complete digitization of innumerous processes makes results achieved by analysis leveraging AI, much more robust. Also, there is an availability of computational power and the capacity to efficiently process large amounts of data at reasonable prices.
Meanwhile, technology has matured well beyond the R&D phase and investment capital targeting this sector is becoming available. An overall assessment shows AI solutions are also used across a variety of other sectors, for example, to control spam, detect frauds, improve the relevance of web search results, translate text and speech, make critical decisions in stock trading, help species conservation, predict weather patterns, make use of energy more efficient – and more. So thankfully artificial intelligence in the futuristic mix can also represent a great opportunity for world sustainability.