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By:

Prasad Dixit

11 October 2024 at 1:09:23 am

The Human Advantage in an Artificial Age

As artificial intelligence grows smarter and more efficient, the real battle may not be about machines surpassing humanity but about whether humans squander the qualities that still set them apart. With the recent news of a Chinese robot beating the human record in a half- marathon, there is renewed debate on how AI could outsmart human beings. Many experts see it as yet another proof of impending disaster as AI takes over most of the jobs in the years to come. This is not the first time when...

The Human Advantage in an Artificial Age

As artificial intelligence grows smarter and more efficient, the real battle may not be about machines surpassing humanity but about whether humans squander the qualities that still set them apart. With the recent news of a Chinese robot beating the human record in a half- marathon, there is renewed debate on how AI could outsmart human beings. Many experts see it as yet another proof of impending disaster as AI takes over most of the jobs in the years to come. This is not the first time when human civilization is facing a technological revolution that has the potential to impact society and economy in a profound manner. There is, however, a crucial difference with AI driven revolution that is often missed out. The first industrial revolution happened because steam engines were invented and it led to mechanization of production. It was followed by discovery of electrical energy and technologies to harness it for mass production. Next wave of evolution was led by computerization and automation in practically all the fields covering both offices and industrial shop floors through mainframes, personal computers, and programmable logic controllers. While all these leaps in technologies are very different in terms of the specific underlying inventions, they all have one thing in common. They were all invented to do things that were humanly impossible to do. One steam engine or electric motor could do the work that perhaps hundreds of humans would never be able to accomplish even with their collective muscle power. Automation of the manufacturing assembly line would deliver speed and accuracy that human beings would never be able to achieve. Beyond Human Technological advances in Telecommunication, for that matter, have simply expanded the range of 'hearing' and 'seeing' far beyond what human vocal chords, ears, and eyes could manage to do on their own. Computers, at its core, are essentially doing the math and calculations at a speed and accuracy that the human brain can never achieve. To add to that, machines using all these innovations in technology would work tirelessly without any fatigue for a duration that human beings would never be able to match. Although AI is yet another highly potent technological innovation, it is not as straightforward as the previous ones. It can absorb and synthesize huge amounts of data that the human brain perhaps cannot do. Ability of AI to answer any question reasonably well using all the global knowledge made available to it, summarize enormous amount of data and text quickly, quickly draw a complex picture based on instructions given verbally, predict a trend, recognize and highlight a specific face in a fraction of a second from millions of faces, write code based on simple English instructions, are all examples where the speed and accuracy of underlying computation is delivering what human being cannot match. However, there are several areas where human beings are trying to improve AI so that it can, some day, match or exceed capability that human beings themselves already have. Examples of this include the ability of AI to completely replace a human driver safely in all situations, understand full context or an intent behind a statement, carry out complex and well-coordinated mechanical activity in response to various unpredictable situations, react appropriately by correctly assessing the emotions at play, integrate generated code appropriately in the existing larger systems landscape, and so on. In such cases, AI is not exhibiting any capability that is humanly impossible to match. On the contrary, AI is trying to catch up with what humans can do easily. In other words, in these areas, AI is trying to become what humans already are. This very aspect separates AI driven technology revolution from all the previous ones. Direct Competition It is often said that AI and humans will co-exist in the future, and people will need to change their ways of working. It is obvious that AI is also going to directly compete with humans in many sectors. Equipment with an embedded chip on-board do compete with humans even today. A case in point is household equipment such as ‘intelligent’ washing machines and dish-washers where robots to do vacuum cleaning and floor mopping do compete with humans offering these services. A human household help can perform these activities far better than what a machine can do. However, given an affordable choice, an increasing number of households prefer machines over human maid services for a reason. Human household help may not always be punctual, sincere, honest, and reliable. But machines are. Uncontrolled emotions, anger, frustration, laziness, indiscipline, absenteeism do affect humans - but not AI driven machines (at least till the time AI itself acquires emotions of its own, and becomes self-aware some day). This aspect of comparison between AI and humans is likely to become far more prominent and consequential as AI driven machines and robots become more and more intelligent and thereby start competing far more effectively with human capability in many spheres. Competition is said to bring about improvement. Just as AI improves itself through continuous learning to mimic human behaviour and actions, human workforce also needs to improve itself by avoiding behavioural issues and inefficiencies referred to above. Otherwise, humans would lose the natural advantage that they still enjoy over AI, and which is likely to continue even in the foreseeable future. Employers or consumers in the labour-intensive service sector will accept AI driven machines and robots with all its known limitations if it turns out to be a better net-net deal in comparison to services offered by humans. This specific aspect has tremendous significance for India. Many Countries from the developed world do not have a young population with reasonably good IQ in required numbers. India, on the other hand, has it in abundance. One could compare it with abundant availability of Thorium or Sunlight in India as compared to the Western world. Consequently, unlike many Countries in the world that have a Uranium centric approach towards nuclear energy, India's approach needs to be centered around Thorium. India's strategy related to renewable, non-conventional, green energy needs to be based on solar power. Indian Context Strategies for adopting AI in the Indian context need to be similarly tailored for the Indian context. India needs to adopt AI in the areas where it clearly has an advantage over humans in terms of speed, throughput, ease of use, accuracy, and efficiency. However, the use of AI needs to be judiciously controlled in areas where AI is trying to catch up with the capabilities of the human mind and body. Several labour-intensive services such as drivers, caregivers for the elderly people, parcel delivery, security guards, maintenance and repair of various equipment, are all examples in that category. Educational policies and overall work culture in the Country needs to appreciate this reality. Just as AI experts are trying hard to 'teach' AI algorithms and improve them through supervised learning, another set of experts need to sensitize and teach humans on how to understand, appreciate, preserve, and further hone the significant natural advantage that they already have over AI. Despite all the technological breakthroughs in AI, in many areas, still, it is a battle that humans will lose only if they choose to. (The writer works in the Information Technology sector. Views personal.)

Forensics in Solving Highway Crashes

Forensic science sheds light on every skid mark, crash, and clue, ensuring justice is served to road crash victims.

Highway Crashes

Highway accidents are one of the leading causes of death and injury in India, with over 1.5 lakh lives lost annually, many on highways. Highways often become hotspots for accidents due to speeding, drunk driving, and poor road conditions. Forensic science uncovers the truth behind such tragic events by applying scientific principles to analyse evidence, removing speculation, and ensuring justice for victims.


In highway accident investigations, tire marks (impressions from stationary or moving tires) reveal the direction of travel, while skid marks (friction marks like skid, yaw, and scuff marks) provide insights into sudden manoeuvres: braking attempts and loss of control. Crash reconstruction tools like 3D modelling and simulations assess impact forces, vehicle speeds, and the sequence of events. By analysing the length, width, and patterns of these marks, experts can identify vehicle types, detect faulty brakes or tire defects, and estimate the collision point.


To extract digital evidence from vehicles, forensic experts first document key details such as the vehicle's make, model, VIN, and odometer reading and conduct a physical inspection with photographs. Using forensic tools like Berla iVe software, they access the infotainment system or other modules. If present, removable media like SIM cards or SD cards are extracted separately. For non-destructive methods, data is retrieved directly, but if deeper access is needed, a chip-off extraction is performed with written approval, as it is destructive. Extracted data, including vehicle speed, braking, GPS logs, and system activities, is analysed to reconstruct events.


Forensic toxicology tests are used to detect alcohol or drugs at the time of the crash. CCTV footage can capture crucial moments of the accident, helping to validate or challenge eyewitness accounts. DNA and blood analysis are used to identify victims, determine the cause of death, and assess the presence of substances. Weather and environmental conditions, like rain or poor lighting, can affect driving conditions. Forensic photography documents the accident scene and helps preserve evidence for legal proceedings. Together, these elements provide a comprehensive understanding of the incident, helping to establish accountability.


Recently in the Pune Porsche Crash (May 2024), forensics revealed the car’s speed of over 150 km/h and the intoxication of the underage driver, ensuring accountability. The Yamuna Expressway Crash (January 2024) exposed tire failure due to improper air pressure, stressing vehicle maintenance. The Cyrus Mistry Accident (2022) underscored the importance of rear seatbelts, while the Balasore Train Tragedy (2023) revealed signal lapses, leading to safety improvements. Actor Salman Khan's car allegedly ran over five people sleeping on a pavement in Mumbai, killing one and injuring four. Salman was accused of rash and negligent driving and fleeing the scene. Four men were charged with intentionally dragging 20-year-old Anjali Singh to death under a car (2023), despite chances to save her, while two others were accused of misleading the investigation. Forensic experts reconstructed the case by analysing the crime scene and examining skid marks, blood traces, and clothing fragments along the route. The car was examined for bloodstains and fibres, while CCTV footage, GPS data, and call records were analysed to track the vehicle's movements and timeline.


Between 2018 and 2022, 2.45 lakh deaths were reported in hit-and-run cases in India, but only 33,212 cases resulted in convictions. Uttar Pradesh and Maharashtra lead in hit-and-run fatalities, accounting for a significant share of deaths. The Supreme Court stated that delay in filing an FIR does not reject motor accident claims unless the evidence is weak or insufficient. Despite a rising conviction rate, improving from 28% in 2018 to 47.9% in 2022, over 2 lakh cases remain pending. With rising highway accidents, strengthening forensic capabilities is crucial.


(Dr. Kumar is a former IPS officer and forensic consultant to Assam government. Das is a student of FSU, Guwahati. Views personal.)

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