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Insights into Editorial: Responsible AI — the need for ethical guard rails

 

 

Introduction: About Artificial Intelligence:

Artificial intelligence is the branch of computer science concerned with making computers behave like humans.

AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making.

Artificial intelligence (AI) refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. Initially conceived as a technology that could mimic human intelligence.

AI has evolved in ways that far exceed its original conception. With incredible advances made in data collection, processing and computation power, intelligent systems can now be deployed to take over a variety of tasks, enable connectivity and enhance productivity.

As AI’s capabilities have dramatically expanded, so have its utility in a growing number of fields.

 

Artificial Intelligence’s exponential growth in recent decade:

  1. It is embedded in the recommendations we get on our favourite streaming or shopping site; in GPS mapping technology; in the predictive text that completes our sentences when we try to send an email or complete a web search.
  2. It promises to be even more transformative than the harnessing of electricity. And the more we use AI, the more data we generate, the smarter it gets.
  3. In just the last decade, AI has evolved with unprecedented velocity from beating human champions at Jeopardy.
  4. Automation, big data and algorithms will continue to sweep into new corners of our lives until we no longer remember how things were “before”.
  5. Just as electricity allowed us to tame time, enabling us to radically alter virtually every aspect of existence, AI can leapfrog us toward eradicating hunger, poverty and disease opening up new and hitherto unimaginable pathways for climate change mitigation, education and scientific discovery.

 

Artificial Intelligence usage can be for better or for worse:

Already, AI has helped increase crop yields, raised business productivity, improved access to credit and made cancer detection faster and more precise.

It could contribute more than $15 trillion to the world economy by 2030, adding 14% to global GDP. Google has identified over 2,600 use cases of “AI for good” worldwide.

A study published in Nature reviewing the impact of AI on the Sustainable Development Goals (SDGs) finds that AI may act as an enabler on 134 or 79% of all SDG targets.

We are on the cusp of unprecedented technological breakthroughs that promise to positively transform our world in ways deeper and more profound than anything that has come before.

 

Challenges of Artificial Intelligence (AI):

  1. Artificial intelligence is poised to be one of the biggest things to hit the technology industry (and many other industries) in the coming years.
  2. But just because it holds enormous potential does not mean it does not also have its challenges.
  3. And artificial intelligence challenges and possibilities are not small, which is why recognizing and working towards resolutions to problems can help further propel artificial intelligence’s rapid growth.
  4. According to studies, around 40 % of the total energy that data centres consume goes to cooling IT equipment. Now, to reduce energy consumption, companies are moving their data centres into cooler climates such as Siberia.
  5. The environmental impact caused by data centres doesn’t stop at electrical consumption.
  6. Coolants are often made of hazardous chemicals, and battery backups at data centres – needed for when there are power shortages – cause an environmental impact both due to mining for battery components and the disposal of the toxic batteries afterward.
  7. Countries are passing stricter legislations on data security that require citizen data to be stored on servers located domestically, picking colder climates beyond their borders is becoming a difficult option.
  8. Robotics and AI companies are building intelligent machines that perform tasks typically carried out by low-income workers: self-service kiosks to replace cashiers, fruit-picking robots to replace field workers, etc.
  9. Algorithms based on our past digital searches creates and provides us probable solutions or alternatives which we are looking for.

Hence, based on our digital footprints, AI is trying to mimic our preferences and even thought perceptions.

 

Privacy issues worries:

  1. AI also presents serious data privacy concerns. The algorithm’s never-ending quest for data has led to our digital footprints being harvested and sold without our knowledge or informed consent.
  2. We are constantly being profiled in service of customisation, putting us into echo chambers of like-mindedness, diminishing exposure to varied viewpoints and eroding common ground.
  3. Today, it is no exaggeration to say that with all the discrete bytes of information floating about us online, the algorithms know us better than we know ourselves. They can nudge our behaviour without our noticing.
  4. Our level of addiction to our devices, the inability to resist looking at our phones, and the chilling case of Cambridge Analytica in which such algorithms and big data were used to alter voting decisions should serve as a potent warning of the individual and societal concerns resulting from current AI business models.
  5. In a world where the algorithm is king, it behoves us to remember that it is still humans with all our biases and prejudices, conscious and unconscious who are responsible for it. We shape the algorithms and it is our data they operate on.

 

Artificial Intelligence usage can be double edged sword:

  1. The study in Nature also finds that AI can actively hinder 59 — or 35% — of SDG targets.
  2. For starters, AI requires massive computational capacity, which means more power-hungry data centres and a big carbon footprint.
  3. Then, AI could compound digital exclusion. Robotics and AI companies are building intelligent machines that perform tasks typically carried out by low-income workers: self-service kiosks to replace cashiers, fruit-picking robots to replace field workers, etc.
  4. Without clear policies on reskilling workers, the promise of new opportunities will in fact create serious new inequalities.
  5. Investment is likely to shift to countries where AI-related work is already established, widening gaps among and within countries.
  6. Together, Big Tech’s big four Alphabet/Google, Amazon, Apple and Facebook are worth a staggering $5 trillion, more than the GDPs of just about every nation on earth.
  7. In 2020, when the world was reeling from the impact of the COVID-19 pandemic, they added more than $2 trillion to their value.
  8. The fact is, just as AI has the potential to improve billions of lives, it can also replicate and exacerbate existing problems, and create new ones.

 

Measures to avoid misusing of Artificial Intelligence:

  1. Without ethical guard rails, AI will widen social and economic schisms, amplifying any innate biases at an irreversible scale and rate and lead to discriminatory outcomes.
  2. It is neither enough nor is it fair to expect AI tech companies to solve all these challenges through self-regulation.
    1. First, they are not alone in developing and deploying AI; governments also do so.
    2. Second, only a “whole of society” approach to AI governance will enable us to develop broad-based ethical principles, cultures and codes of conduct, to ensure the needed harm-mitigating measures, reviews and audits during design, development and deployment phases.
  3. To inculcate the transparency, accountability, inclusion and societal trust for AI to flourish and bring about the extraordinary breakthroughs it promises.
  4. Given the global reach of AI, such a “whole of society” approach must rest on a “whole of world” approach.
  5. Many countries, including India, are cognisant of the opportunities and the risks, and are striving to strike the right balance between AI promotion and AI governance both for the greater public good.
  6. NITI Aayog’s Responsible AI for All strategy, the culmination of a year-long consultative process, is a case in point.
  7. It recognises that our digital future cannot be optimised for good without multi-stakeholder governance structures that ensure the dividends are fair, inclusive, and just.

 

Conclusion:

The UN Secretary-General’s Roadmap on Digital Cooperation is a good starting point: it lays out the need for multi-stakeholder efforts on global cooperation so AI is used in a manner that is “trustworthy, human rights-based, safe and sustainable, and promotes peace”.

And UNESCO has developed a global, comprehensive standard-setting draft Recommendation on the Ethics of Artificial Intelligence to Member States for deliberation and adoption.

Agreeing on common guiding principles is an important first step, but it is not the most challenging part.

It is in the application of the principles that the rubber hits the road. It is where principles meet reality that the ethical issues and conundrums arise in practice, and for which we must be prepared for deep, difficult, multi-stakeholder ethical reflection, analyses and resolve. Only then will AI provide humanity its full promise.