Four ways in which AI can help humankind

 

Artificial Intelligence is receiving more than its fair share of public attention. On one side there are promises of miracles, while on the other side there are warnings of doomsday. What is probably missing is a simple listing of clear benefits. This is article is an attempt to create such a list.

Artificial Intelligence is more of an ambition than a technology. The ambition is to imitate human capabilities. Since human capabilities range from walking to solving mathematical problems, AI also encompasses systems of various types – ranging from the humble calculator to Google’s DeepMind.

In this article, I am majorly referring to the AI systems that try to achieve the cognitive abilities of human beings. Cognitive abilities refer to the processes of our mind such as understanding, reasoning, planning and selecting the right action. Understanding a question and supplying the right answer from our memory is an example of cognitive ability, the one that AI systems called ‘chatbots’ try to imitate.

Cognitive systems are currently in their initial phase of development. Once they come close to human beings in their competence, they can prove useful to humankind in a number of ways. Here are some:

1.    Better utilization of resources: In our current world, it requires a human being to use resources. For example, a car needs a driver. Platforms like Uber have made it possible to share your car when you don’t need it, but it still requires a skilled human being. Talk to your Ola or Uber driver and you will realize that they are already working at the limit of their capacity. A cognitive system driving vehicle will use them much more efficiently. You will actually need much fewer vehicles than you need today (and probably a lot lesser parking!). This is true of most other resources.

2.    A fairer society: Human beings have many faults in their thinking. In another article I have highlighted this faults, called biases. These biases have their roots in the evolution, so the AI systems will (hopefully) not have them. ( Pl see http://blog.cerelabs.com/2017/06/will-ai-evolve-to-be-as-bad-as-humans.html). This will make decision making at all level fairer for the people. To take an example, typecasting is a very strong bias that we suffer from. This affects decisions taken by, say an interviewer. We can hope to see much fairer selection processes in the future. For an interesting example of how statistics can help to break biased notions, see the movie or read the book ‘Moneyball’.

3.    Repositioning of human efforts: World over, a large number of people are engaged in time consuming tasks that require moderate cognitive ability. Take for instance cooking. A big part of a woman’s day in India is spent in preparing food. Cognitive systems such as robot chefs can easily take over these jobs, freeing up a lot of time that can be invested in more valuable responsibilities like education of the children. In the industries, as the simpler tasks are done by cognitive systems, humans can move up the value chain, pushing the efficiency of the enterprise higher.

4.    Improved care: Currently, care of patients, elderly and disabled is primarily a human responsibility. Many times, this compromises the quality of care as people cannot take out so much time from their daily activities. Cognitive systems can make the life of those in need of care much better. They can talk to the elderly and carry the disabled to places otherwise difficult to reach. The systems can keep an eye on chronic patients, not just reminding but making sure their regimen is adhered to.

This is of course just a small contribution to an ever growing list of benefits. While we keep our eyes open to the warnings given by the likes of Stephen Hawking and Elon Musk, we should continue in our efforts to harness the power of AI for these benefits.

By Devesh Rajadhyax

Co-Founder, Cere Labs


Comments

Post a Comment

Popular posts from this blog

Can language models reason?

Image
  Illustration by Rajashree Rajadhyax Large language models are an impressive technology that excels at providing answers based on vast knowledge of the world. However, they often struggle with reasoning and logic-based questions. To overcome this limitation, the Chain-of-Thought (CoT) method was introduced. This technique emulates how humans solve problems by reasoning step-by-step. Just as we break down complex problems into smaller, manageable parts for analysis and logical resolution, CoT guides language models to adopt a similar approach. By mimicking this natural, structured problem-solving process, CoT enhances the models’ ability to handle logic-driven tasks with greater accuracy and reliability. This approach, however, requires more time and computational effort because it involves processing more tokens . Tokens are the building blocks of text, like words or parts of words, that the model uses to understand and generate responses. Since the Chain-of-Thought method involv...
Read more

AI implementation myths

Image
  Visionary leaders recognize the importance of adopting cutting-edge technologies to enhance their business operations. This is a bold move, especially in the early stages when few businesses have embraced it. Generative AI is currently at such a juncture. Although AI has experienced several setbacks over the years, recent advancements in foundational models like large language models (LLMs) have reignited interest and investment in the field. Generative AI never fails to impress those who see it in action. At Cere Labs, my company, we have developed a Gen AI framework, and whenever I demonstrate it, the feedback is unanimously positive, with many stating it is "useful." However, despite this enthusiasm, there is hesitation when it comes to integrating this technology into business practices. Addressing certain misconceptions and concerns could help leaders more easily adopt Generative AI to enhance their operations. With my 8 years of experience assisting businesses in inco...
Read more

Homework 2.0: The science behind homework and why it still matters in the AI age!

Image
  Illustration by Rajashree Rajadhyax I recently came across an article about how teachers are coming up with methods to distinguish between homework done by students and that done by AI. This effort by teachers is not without cause; a recent case in Massachusetts saw a student penalized for using AI in their history paper, highlighting the need for such measures. I found it intriguing and couldn’t help but reflect on this shifting trend.  Homework! Does that word bring back memories? The race to finish it as fast as possible so you could finally go play! Holidays would’ve been so much better without it, don’t you think? I know I felt that way, and I’m pretty sure you did too. And let’s not forget those classmates with endless excuses for not doing it. The most common one? “I wasn’t feeling well!” 🤒 Some would even throw in a few coughs just to make it believable 😏. I was that kid on the opposite end. Just before a holiday, I’d be sneaking in some homework during lunch break...
Read more