AI’s Potential and Threat Call

In News

• Artificial Intelligence (AI) in recent years has emerged as a transformative phenomenon. 

About Artificial intelligence

• About:
  • It is the science and engineering of making intelligent machines, especially intelligent computer programs. 
  • It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.
• Significance:
  • AI would not replace people but create new opportunities in various fields. 
  • It works on data, and if we could train our machines, it could do wonders for us in milliseconds by automating processes. 
  • AI is creating new opportunities which could not be achieved by traditional technology.
• Applications:
  • Social benefits:
    • AI is being largely used for socially beneficial ends. 
    • For example, AI is being used to develop new medical treatments, improve crop yields, create more efficient transportation systems, reduce crime rates, improve education and protect the environment.
  • Speech Recognition: 
    • It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. 
    • Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting. 
  • Computer Vision: 
    • This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. 
    • This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry.  
  • Automobiles: 
    • While self-driving vehicles are not yet standard, cars already use AI-powered safety functions. The EU has for example helped to fund VI-DAS, automated sensors that detect possible dangerous situations and accidents. Navigation is largely AI-powered.
  • Cybersecurity: 
    • AI systems can help recognise and fight cyberattacks and other cyber threats based on the continuous input of data, recognising patterns and backtracking the attacks.
  • Fighting disinformation: 
    • Certain AI applications can detect fake news and disinformation by mining social media information, looking for words that are sensational or alarming and identifying which online sources are deemed authoritative.
  • Smart homes, cities and infrastructure:
    • Smart thermostats learn from our behaviour to save energy, while developers of smart cities hope to regulate traffic to improve connectivity and reduce traffic jams.
  • Transport: 
    • AI could improve the safety, speed and efficiency of rail traffic by minimising wheel friction, maximising speed and enabling autonomous driving. Tesla Cars use AI.
  • Agriculture:
    • AI applications in agriculture have developed applications and tools which help farmers inaccurate and controlled farming by providing them proper guidance to farmers about water management, crop rotation, timely harvesting, type of crop to be grown, optimum planting, pest control etc. use of drone to analyze the captured images and provide a detailed report containing the current health of the farm. 
    • It helps the farmer to identify pests and bacteria helping farmers to timely use pest control and other methods to take required action.
  • Health: 
    • It can be used for diagnostic purposes for various diseases, including COVID-19, and could prove very effective in remote areas where adequate health facilities are not available.
    • Artificial intelligence against Covid-19: 
      • In the case of Covid-19, AI has been used in thermal imaging in airports and elsewhere. 
    • In medicine it can help recognise infection from computerised tomography lung scans. It has also been used to provide data to track the spread of the disease. 

Challenges

• The challenge & fears of unknown:

• The biggest challenge in achieving this balance is that no one knows for certain what’s going to happen next with AI. 
• There are widespread fears. These range from apocalyptic scenarios such as AI posing an existential threat to humans, to more immediate fears, which include developing deepfakes that can be used to spread misinformation, create identity theft tools, more effective cyberattacks and automate tasks that are currently done by humans. 

• Difficulty to control:
  • This technology is evolving so fast that stakeholders are falling behind miserably when it comes to putting safeguards. 
  • There have been calls to pause development of AI to give time for governments and industry players to come up with guardrails. 
  • But the horse has already bolted, and at a good speed. There is competition between governments, universities and companies, all seeking to advance the technology, so it will be impossible to impose a worldwide moratorium. 
• Lack of regulations:
  • It is clear that there is a global race for AI dominance. Nations across the world are investing heavily in AI research, development, and deployment. 
  • While healthy competition can drive innovation, an unregulated race can lead to a fragmented landscape where standards, ethics, and accountability fall by the wayside. 
  • Unregulated AI can also deepen social inequalities in addition to posing threats to privacy and civil liberties.

Suggestions

• Setting an international standard:
  • To prevent a dystopian future and ensure a collaborative approach, it is essential to have international agreements and standards for AI development and use. 
• India’s lead:
  • While countries including the UK and US are still debating the need for regulations, India can take the lead. 
  • In his recent visit to India, Open AI CEO underscored India’s role in the global conversation on what this regulatory framework could look like. 
• Collective participation in regulations:
  • Regulations cannot be left entirely in the hands of the industry, given the power of this technology. Its revenue models are closely linked to data collection. 
  • Governments, industry leaders, and academia must work together to develop transparent guidelines, ethical frameworks, and regulatory structures with enough teeth to deter bad actors. 
• The regulations:
  • These regulations should cover areas such as data privacy, algorithmic transparency, accountability, and safety standards for AI systems.
  • Care should be taken that regulations do not stifle innovation, but rather ensure that its development is aligned with ethics and individual rights.

• Combating the misuse:
  • Efforts to combat the misuse of AI should involve international cooperation and information sharing. 
  • This can address the potential threats posed by malicious actors who exploit AI for cyber warfare, propaganda, or other destructive purposes. 

Way ahead

• Artificial Intelligence (AI) has emerged as a transformative phenomenon , revolutionising various industries and unlocking countless possibilities. 
• However, as AI continues to evolve rapidly, it is imperative to strike a balance between fostering innovation and ensuring ethical use.