In the ever-evolving landscape of technology, artificial intelligence (AI) stands as both a beacon of innovation and a source of concern. From the perspective of Hindu philosophy, which emphasizes harmony (samatva), balance (santulan), and interconnectedness (sahcharya), the future with AI holds immense potential for positive transformation. However, it also presents unique challenges and risks that must be carefully navigated. In Hinduism, the concept of dharma, or righteous duty, guides individuals towards actions that uphold the greater good and foster harmony within society and the cosmos. From this perspective, a positive future with AI entails leveraging its capabilities to enhance human welfare, promote sustainability, and advance spiritual evolution.

One of the most promising aspects of AI is its capacity to revolutionize various sectors, including healthcare, agriculture, education, and environmental conservation. Through AI-driven innovations, such as predictive analytics in healthcare, precision agriculture, personalized learning platforms, and climate modeling, humanity can address pressing challenges more effectively. This aligns with the Hindu principle of seva, or selfless service, wherein individuals work for the welfare of all beings. Furthermore, AI has the potential to foster interconnectedness and global unity by transcending barriers of language, culture, and geography. Platforms powered by AI, can facilitate cross-cultural communication and understanding, promoting the Hindu ideals of vasudhaiva kutumbakam (the world is one family) and sarva dharma samabhava (equal respect for all faiths).

Despite its potential benefits, AI also poses significant risks and challenges, particularly from a Hindu standpoint. One prominent concern is the erosion of human autonomy and the loss of control over decision-making processes. That erosion is already forecast in the plans for an AI-controlled city in Abu Dhabi. In Hinduism, the concept of free will (purushartha) is central to the notion of spiritual growth and karmic responsibility. Therefore, any AI systems that undermine human agency could pose a threat to the fundamental principles of dharma and moksha (liberation). We have a saying in Sanskrit: उद्देश्यपूर्ण जीवन हो तो वो उत्सव कहलाता ह. This means that life becomes a celebration if there is a purpose in it. Otherwise we are dragging it along with no idea where we are taking it. What we are witnessing these days, with the emergence of the AI, is that we are being robbed of our purpose. For the first time in the history of this planet there is a revolution and we are not part of it – this revolution of a totally automated world which is being steered by AI. Human beings are slowly becoming irrelevant. My biggest worry is that everything will be controlled by the algorithms drafted by the AI. Suddenly we would have a plethora of disillusioned people with absolutely no clue if their existence is going to make any difference.

Additionally, AI-driven algorithms may perpetuate biases and discrimination, leading to social injustice and inequality. For instance, if AI-powered hiring tools favor certain demographics over others, it could exacerbate existing disparities in employment opportunities, contradicting the Hindu ideal of social equity (samta) and dharma-based governance. Moreover, there are concerns about the ethical implications of AI, particularly in the context of privacy, surveillance, and data security. In Hinduism, the concept of aparigraha (non-possessiveness) emphasizes the importance of respecting individuals’ privacy and autonomy. Any misuse of AI technologies that infringes upon these principles is antithetical to Hindu values.

To address these risks and move towards a positive vision of the future with AI, we not only need ethical frameworks and a human-centric design. We also need truly interdisciplinary collaboration. The future with AI holds immense potential for positive transformation, guided by the principles of harmony, compassion, and spiritual evolution inherent in Hindu philosophy. However, to realize this vision, it is imperative to address the associated risks and challenges, including but not limited to those mentioned above. By embracing ethical frameworks, prioritizing human values, fostering education and awareness, promoting interdisciplinary collaboration, and empowering individuals, we can navigate the complexities of AI and move towards a future that upholds the ideals of dharma, unity, and holistic well-being. In 1987, Pandit Shriram Sharma Acharya ji, a prolific scholar of modern India and found of Gayatri Pariwar, offered some reassurance about current times that are still relevant today. He said that while the current circumstances look dark and gloomy, they should not bring fear or despair to us. Rather, we should embrace them as a call to action. They are a sign that we are born at a time when entire mankind is called to accomplish a completely new level of collaboration between different nations, races, religions, sectors and societies. For the first time in history, all the people of the world are called to work together as a single human family. AI, knowingly or unknowingly, has given us such an opportunity.

If there is one factor that contributed most to society’s progress, it is intelligence. We have progressed from living in caves to living in electrified houses with clean water and a quality of life that would have seemed like a sheer utopia if our ancestors had been able to even imagine it. At the same time, intelligence contributes to the biggest risks to humanity – without intelligence, we would have no nuclear energy but also no nuclear bombs. 

Transformative AI could amplify both the societal benefits and risks of intelligence. But contrary to the emergence of human intelligence, we have an opportunity to shape AI’s development: What goals could society achieve with AI? What institutions already exist for this purpose? Can we learn from their successes and shortcomings to build institutions better designed to leverage transformative AI for good?  

To explore these questions, Foresight Institute and the Future of Life Institute gathered leading researchers in AI, policy, law, economics, and related fields for a two-day event in February 2024: the Existential Hope Transformative AI Institution Design Hackathon. The goal was to design institutions that can guide the development of Transformative AI for the benefit of humanity. Institutional proposals were judged based on how well they would work, how realistic they were, and the positive impact they could have. If you are curious to learn more about the hackathon procedures and outcomes you can learn all about it in our detailed hackathon report.

Here are the three winning institutions:

1. Can AI Make Us Happier? The Flourishing Foundation’s Proposal for a Human-Centered Future (Hackathon Winner)

The Flourishing Foundation is an independent innovation lab that tackles the question: can AI make us happier? Their mission is to ensure that powerful new technologies like AI benefit humanity and the planet.

This interdisciplinary group of scientists, designers, engineers, and artists believe technology should strengthen our connections – to ourselves, each other, and the natural world. They advocate for “life-giving” economic systems, arguing that deploying AI within current economic structures won’t necessarily improve well-being.

The Flourishing Foundation takes a systems-thinking and life-centric design approach. Here’s how:

1. Operationalize Research: Translate interdisciplinary research into knowledge frameworks that better guide conscious technology creation: e.g. alternative well-being based success metric for consumer tech products and services other than “engagement”
2. Incubate Products: Provide holistic and hands-on support for innovators to design and run experiments with a focus on conscious/humane use of transformative technologies: e.g. AI-enabled solutions for elderly care and family connection
3. Build Movement: Build awareness by mobilizing innovator communities to channel their creative energy towards conscious tech creation: e.g. weekly meetups, quarterly build days, and symposiums.

2. AI for Democracy? The Global Deliberation Coordinator Aims to Revolutionize Global Decision-Making (Shared Second Place)

The Global Deliberation Coordinator (GDC) is a new approach to global decision-making through “Global Deliberation as a Service” (GDaaS). GDC is a coordinating body that works with partners around the world to convene a representative microcosm of the planet — and equip them with the structure and resources needed for high-quality deliberation.

These global deliberations can be utilized by international organizations, governments, and companies to prove input or make critical decisions that put “humanity in the loop”. Through an advanced market commitment, pilot projects, and integration of cutting-edge AI and deliberative technology, the GDC seeks to demonstrate the feasibility and impact of this new model.

By making global deliberative processes more accessible and impactful, the GDC aims to strengthen humanity’s collective decision-making capabilities in the face of planetary challenges like artificial intelligence development and climate change. GDaaS offers a powerful new tool for incorporating the considered will of the people into how we navigate the crucial choices ahead.

3. Preparing for the Unexpected: Transformative Simulations Research Institute (Shared Second Place)

The Transformative Simulations Research Institute (TSR) is a new organization dedicated to rigorously modeling how individuals, groups, and societies may respond to the emergence of transformative artificial intelligence (TAI) capabilities. As TAI systems grow more powerful, there are risks of misaligned or adversarial development that could destabilize or threaten humanity.

To help mitigate these risks, TSR employs cutting-edge simulation techniques like wargaming exercises, computational games, and human-led scenario roleplays to systematically investigate potential TAI trajectories from multiple perspectives. By developing an empirically-grounded, multidisciplinary understanding of the cognitive patterns, social dynamics, and ethical issues that may arise when advanced AI intersects with human actors, TSR aims to equip policymakers and technologists with crucial foresight.

TSR’s goal is to steer transformative AI development toward robustly beneficial outcomes that safeguard human flourishing over the long term. TSR’s simulations chart the vast possibility space of TAI-enabled events and human decision pathways, identifying potential pitfalls but also constructive governance frameworks. The institute pioneers novel experiential modeling approaches to reality-test our assumptions and future-proof society against catastrophic AI failure modes as this powerful technology advances.

A hackathon can excite institutional prototypes but the real work lies in realizing them. To incentivize and support the continuation of the work initiated during the hackathon, the winning team was awarded $10,000, and the two teams that were selected as runners-up, each received $5,000. To put these ideas into action, each proposal – The Flourishing Foundation, the Global Deliberation Coordinator, and the Transformative Simulations Research Institute – are currently being incubated into real-world institutions. We look forward to following their evolution. 

To provide efforts like this with the support they need, The Future of Life Institute launched its Futures program: This program aims to steer humanity toward the beneficial uses of transformative technologies, including offering funding opportunities for research on safe AI applications to improve the world. 

To offer a recurring forum for envisioning beneficial AI worlds, The Foresight Institute launched its Existential Hope Worldbuilding Course: This course focuses on exploring AI in various future scenarios, promoting optimistic visions of AI solving global challenges.

We extend our gratitude to all who contributed – from our hackathon teams, to the judges, mentors, and the Future of Life Institute. Stay tuned for further updates on the implementation of these ideas!

Resources

• TAI Institution Design Hackathon Report
• FLI Futures Program
• Foresight Institute’s Existential Hope Program
• Foresight Institute’s Existential Hope Newsletter

France’s 300 nuclear weapons were useless to protect them from the horrendous suicide bomb attacks in Paris on Nov. 13, 2016. And if France ever uses those weapons to attack another country’s cities and industrial areas, France itself will become a suicide bomber. Mutually assured destruction gave way to self-assured destructionyears ago when we discovered that, even if a country launches a successful nuclear strike against their enemy, the resulting nuclear winter could kill billions more around the world, including the attacking country’s own citizens. The climate effects of the smoke generated from fires from those attacks would last for more than a decade, plunging our planet into such cold temperatures that agricultural production would be halted or severely reduced, producing famine in France and the rest of the world.

The chance of the use of nuclear weapons by mistake, in a panic after an international incident, by a computer hacker, or by a rogue leader of a nuclear nation can only be removed by the removal of the weapons themselves.

As the important climate negotiations at the 21st Conference of the Parties in Paris in December 2015 continue, we have to keep in mind that the greatest threat to our planet from human actions is not global warming, as important as this threat is, but from the accidental or intentional use of nuclear weapons. We need to ban nuclear weapons now, so we have the luxury of addressing the global warming problem.

Follow Alan Robock on Twitter: www.twitter.com/AlanRobock

This article was also featured on the Huffington Post.

German

The following paper was written and submitted by Eric Gastfriend. The information he presents is helpful to keep in mind as we consider the speed with which technologies are advancing today.

90% of All the Scientists That Ever Lived Are Alive Today

This simple statistic captures the power of the exponential growth in science that has been taking place over the past century. It is attributable to Derek de Solla Price, the father of scientometrics (i.e., the science of studying science), in his 1961 book Science Since Babylon. If science is growing exponentially, then the major technological advancements and upheavals of the past 200 years are only the tip of the iceberg.

The implications of exponential growth are notoriously difficult for us humans to wrap our minds around. Legend has it that when the game of chess was invented, the king of India was so taken with the game that he offered the game’s inventor any reward he wished for. The inventor asked for grains of rice – specifically, one grain for the first square of the chessboard, two grains for the second square, four grains for the third square, and so on doubling for each of the 63 squares. The king laughed and granted this request, considering it to be a meager request for so grand an achievement. The king, along with any schoolchild who has heard this story, was surprised to learn that to fulfill this request would require 1,000 times more rice than exists in the world, and would be the size of Mt. Everest. Our intuition is not built to handle the concept of exponential growth.

Luckily, unlimited exponential growth is impossible on Earth (otherwise, we’d be left with no Earth). Although we still hear de Solla Price’s statistic repeated today, we need to ask, does this fact from over 50 years ago still hold true? Is science still increasing exponentially?

tl;dr: Yes and yes.

Price correctly argued that the trend could not continue indefinitely, or we would have more scientists than people (zombie scientists?). However, he also thought that science was already reaching “saturation” in 1961. David Goodstein, a physicist at Caltech, gave a speech in 1994 arguing that The Price Was Right and we had already hit “The Big Crunch” where progress in science slows down, based primarily on data from the US.

In order to investigate this question, I gathered data on 3 indicators of the growth of science: the number of PhD’s granted per year, the number of patents issued, and the number of papers published. For all of these, I have sought to get worldwide data, or at least data from the major countries.

For PhD’s granted, I was able to find data for the US, UK, Australia, India, and China, from each country’s ministry of education website. Data for the US goes back to 1900, but for most of the other countries it only goes back to 1999, so I used a linear extrapolation for those countries back to the date when the first PhD’s were granted for that country. The chart shows that the US grew exponentially until 1971 when it started to level off. But in the 80’s, with Deng Xiaoping in office in the wake of the Cultural Revolution, China begins to pick up the slack, such that the overall world production of PhD’s continues to grow exponentially. In 1961, de Solla Price noticed that the number of scientists was doubling roughly every 15 years. My data show that since 1961, this rate has slowed down slightly, with a doubling roughly every 18 years. Still growing pretty freakin’ fast.

Calculating the percentage of scientists currently alive involves some guesswork. If we assume each scientist is 27 years old when they receive their PhD, and 80 years old when they die, then in my model the PhD grantees from 1959-2012 are alive, and those from 1900-1959 are dead (my apologies if I have given you an untimely death). By that measure, exactly 90% of all scientists that ever lived are currently alive. Of course, this ignores scientists that lived before 1900, although I expect that number to be small relative to the millions of scientists alive today. Technically, de Solla Price said it was 80-90%, so within that range of uncertainty, the statistic probably still stands.

This extrapolation shouldn’t affect the results too much because compared to the US, these countries all had relatively few PhD’s being granted in 1999.

As you can tell from a quick glance at the chart, growth in patents has continued to be exponential. If you look closely at these charts, you can see the impact of many historical events. For example, the fall of the Berlin Wall and end of the Soviet Union brought patent grants to nearly 0 in 1991. Similarly, 1991 cause a huge drop in patent grants in Japan, since that was the year the Japanese economic bubble popped. WWI and WWII both caused drops in global patent issuance. You may notice that the global total seems to drop off a little at the end – this is due entirely to a 20% drop in patents granted in Japan in 2014, which is a time-lag effect of the 2008 financial crisis. The growth rate is similar to that of PhDs, with a doubling roughly every 19 years since 1961.

Papers Published

Analysis of scientific papers published, which was pioneered by de Solla Price, has been well-studied in the academic literature. The most recent, most broad, and most sophisticated analysis I’ve found comes from the paper “Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references” by Lutz Bornmann and Rüdiger Mutz. This paper, along with others in the field of scientometrics, confirms the exponential growth of science – it “has become today a generally accepted thesis.” They show that in the second half of the 20^th century, the number of papers published annually was doubling every 9 years.

For patents granted, the data up to 2006 comes from the WIPO Statistics Database, and after that comes from WIPO and individual countries’ patent office websites. The EPO is the European Patent Office, founded in 1977. The data show it has eclipsed national European patent offices in importance, as part of the trend of greater European integration.

Note that the apparent drop-off at the end of this chart is just an artifact of their estimation technique – they are looking at citations from papers published in 2012 to count papers published in previous years, so the most recent papers haven’t had enough time to be cited yet.

The graph on the left closely resembles Derek de Solla Price’s original curve, showing exponential growth in Physics abstracts, 1900-1950 (graph on the right).

Possible Objections

You might be willing to accept the data presented above, but still disagree with the conclusion that science is actually advancing exponentially.

Objection: Science is Getting Harder

When Sir Isaac Newton discovered the law of gravity in 1665, there weren’t many other scientists around, so there were a lot of low-hanging fruit (get it?). Revolutionary scientific discoveries used to happen quite frequently, but we’re unlikely to get anything as revolutionary as General Relativity in the coming decade. In other words, the recalcitrance or difficulty of making scientific discoveries may be growing exponentially even faster than the number of scientists we’re throwing at the problems.

I think this is true, but there’s a countervailing force to consider. Science builds on itself. Advances in statistics lead to advances in machine learning; the progress of electrical engineering that powers Moore’s Law makes those advances in machine learning practical; and those techniques benefit fields ranging from computational biology to social network theory. So while it’s vastly more difficult for an individual scientist to make significant breakthroughs today, there’s a million-fold multiplier on even small advances from all the scientists worldwide who can build upon that work.

Objection: We’ve Lowered our Standards

Sure, we’re producing more people with the letters PhD at the end of their name, and we’re publishing more papers, but it’s become meaningless. Most published research findings are false. Patents get granted for ridiculous things. The rapid growth of China’s PhD programs may have come at the expense of quality.

There may be some truth to this argument, but let’s see what it implies. Suppose that in the glorious scientific past, in the year 1900, 2/3 of published research findings were replicable, and that now it’s only 1/3. We calculated above that the total number of papers published doubles roughly every 15 years, which means we have had 7 doublings in the 20^th century. If the quality has been cut in half since then, we would be left with 6 doublings of “quality science.” That’s not enough to break the argument. Besides, we should be careful not to glorify the past. Would Freud’s work pass for respectable science today?

Conclusion

Science and technology have drastically transformed our lives. This revolution has taken place almost entirely in the past 200 years – one tenth of one percent of our species’ 200,000 year history. Never before have we had so many people whose sole purpose of work is to better understand how the world works. This has far-reaching implications, both good and bad, for the future of humanity. It’s difficult to wrap our minds around the blistering pace of innovation that is about to come.

As Mr. Bean once said, “Brace yourselves.”

Special Thanks to my research assistant Eitan Kling-Levine for helping me gather this data.

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