The memories of COVID-19 are indeed unforgettable. While the pandemic brought pain and sorrow to this world, it even gave a new sun that shone to heal human beings. The world started following new trends, which were unimaginable, or you can say, bookish enough to be implemented, as no human contact was safe. But, the big round of applause goes to robots and AI to contribute to medical sciences and help doctors, pharmaceutical giants, and ordinary people survive the pandemic.
Kai-Fu Lee, in one of his chapters, “Contactless Love” from the book “AI 2041. Ten Visions for Our Future,” draws attention to the futuristic world where COVID-19 continues even after vaccines, as the new variants of coronavirus keep on emerging. He emphasizes that humans must learn to live with such situations and reduce person-to-person contact by relying on everyday household robots.
The chapter unearths questions, such as how COVID-19 made people follow new trends, which could be positive, including the discovery of new drugs, precision medicine, and surgeries performed by robots with the help of Artificial Intelligence (AI). Furthermore, the author describes how AI will drastically alter conventional medicine, and the field of robotics will become an essential part of the world.
AI and Healthcare Goes Hand in Hand
The revolution in medicine in the 20th century helped increase life expectancy by 31-years. And now, the positive intrusion of AI into the healthcare system is another revolution. This new insurgency involves digitization that will enable all data technologies.
For instance, existing healthcare databases will be digitalized. This will include patient records, medical instruments, devices, clinical trials, drug effectiveness, data related to infectious diseases, drugs supply, and vaccines. One of the prime examples of this digitization is the shift of radiology from back-lit film to HD 3D imagery.
Likewise, physicians and AI will be able to perform medical procedures or even give prescription drugs to patients without making any mistakes. AI will learn from the billions of medical cases and their results in the past and provide personalized treatment to all the patients accordingly.
Is Digitization Just a Myth?
Even though the previous statements appear to be “yet-to-achieve,” it seems like the healthcare sector is already on the verge of transformation.
Digital outcomes through technologies can be seen in almost every infamous healthcare infrastructure. Like, for example, DNA sequencing provides digital information. One can detect pathogens (such as COVID-19) and gene mutations (such as new cancer markers) with the help of Digital Polymerase Chain Reaction (dPCR) and many more.
Therefore, all these examples assure that digitization is an actual concept that has been serving human beings in the healthcare setup. As a matter of fact, drug and vaccine discovery are all set to enter the digitization mode and begin to connect with AI.
The Past Attempts Turned into Failure but Lessons Learned For the Future
In the past, AI projects in the healthcare industry became unsuccessful due to the lack of accurate training. When IBM Watson and its program for cancer treatment joined hands with Sloan Kettering and MD Andersons, these institutions decided to rely on human expertise to train AI.
The datasets used to train AI were inadequate and had lack of concepts. Moreover, the information was derived from medical texts, such as research papers and textbooks, produced for human learning. However, AI is meant to learn from “real-treatment-and-outcomes” data.
But the author believes that through a pragmatic and data-centric approach, Artificial Intelligence in healthcare will shine in the next twenty years.
AI Rising Above the Traditional Healthcare System
Conventional vs. AI Protein Folding, Drug Screening, and Drug Discovery
The conventional method for drug discovery includes four steps:
Step 1: Using mRNA sequence to obtain pathogen’s protein sequences.
Step 2: Finding the 3D structure of the pathogen’s protein sequences (also called protein folding).
Step 3: Identifying the target on the 3D structure.
Step 4: Generating suitable treatment molecules and choosing the ideal preclinical candidate from them
In conventional drug discovery, all four steps above must be done in a proper sequence. However, the last three steps are extremely time-consuming and require high costs.
Kai-Fu explains that it takes $1 billion and several years to achieve a successful vaccine through the conventional development process. But using AI will lower the cost and make the drug available sooner. For example, to obtain protein folding (step 2), DeepMind developed “AlphaFold 2” in 2020, using AI technology and a deep learning structure. And to date, it is one of the most outstanding achievements in the history of science.
While the traditional way of protein folding takes years, AlphaFold can do the same work faster, as the results are more accurate. Similarly, AI can help the healthcare sector find a target on the 3D structure (step 3) and later choose the best biomolecule (step 4).
Insilico Medicine announced the first AI-discovered drug for idiopathic pulmonary fibrosis in 2021. And, gladly, the company saved 90% of the cost that was previously required for performing the above steps using the conventional method. Therefore, proving itself better than the traditional drug discovery. The author believes that AI will cover more areas in the field of drug discovery in the future.
Individualized Precision Medicine and AI
Precision medicine is a way to treat patients individually as per their condition. Since digitization would help attain digital information for each patient, such as medical history and DNA sequencing, it will become easier to provide precision medicine. Again, the credit goes to AI that will make it happen.
Diagnostic AI
AI will surpass doctors in the next twenty years. The technology will help make diagnoses simple, and doctors will only be left to “rubber-stamp” the outcomes.
Robotic Surgeries
Between 2012 and 2018, robot-assisted surgeries have increased from 1.8% to 15.1%. Also, semi-autonomous procedures are being performed through robots, which work under the supervision of doctors, including teeth implants and colonoscopy.
With all the evidence, the author believes that nanobots will be capable enough to perform complete surgeries within the next two decades without the involvement of human doctors. They will be able to fight cancer, repair damaged cells, and eliminate diseases by replacing the molecule DNA.
Increased Life Expectancy
Lastly, AI will be able to plan and prepare supplements, sleep, medication, and therapies for each individual to live a healthy lifestyle. Some experts even believe that people might live twenty years more than the present life expectancy.
The Role of Robots in the Next Twenty Years
Robots Under Industrial Setup
In today’s world, robots are being utilized in most elite industries. For instance, autonomous mobile robots (AMRs) and autonomous forklifts can see and identify obstacles in their way and plan their movement accordingly to move and keep the cargo in a warehouse.
Likewise, robotic arms can grab solid objects when it comes to welding jobs, assembling lines, or picking objects in big e-commerce distribution centers.
Nevertheless, the author believes that these robots will become more eligible to perform tasks just like humans do. For example, robotic arms will have soft skins so they can easily hold fragile items. And similarly, they will learn more by trial and error or by learning from humans by watching their actions.
In the same way, robotics will help the agriculture side by providing services to seed and harvest lands. As a result, robots will help decrease the cost of agriculture and increase food production.
Robots Under Commercial and Consumer Setup
In the future, robotic technologies will be available at a lower cost, allowing its reach to mass audiences. For example, robots, which are now used for serving coffee in a shop, will be used in homes.
Kai-Fu also shares his experience of receiving packages in his apartment complex through robots during the COVID-19 lockdown in China. He also informs that fully automated delivery vans are already under the testing phase in Silicon Valley. That means, by 2041, there will be more advancement in the delivery system.In the same way, there’s a possibility that robots will be used in different positions, such as cleaning laundry, receptionist in an office, and more.
In conclusion, Kai-Fu is optimistic that AI and robotics will change all the world’s essential industries. And its significant effects will be seen in the healthcare industry by 2041.
Tag Cloud
Agile - Agile Delivery - Agile Team - AI - amazonecommerce - Animal Framework - app retention - Attracting talent - Autonomous weapons - B2B - blockchain - businessbuilding - Business building - Clean code - Client consulting - cloud platform - Code Refactoring - coding - Company building - Computer Vision - Corporate startup - cryptocurrencies - de-risking business building - Deepfakes - Deep Learning - DeepMind - derisking business building - design company - Design Research - design thinking - Developer Path - DevOps - Digital Ownership - Digital Product Roadmap - Digital Product Strategy - ecommerce - entrepreneurs - Figma - founder equality - founder equity - front end developer - Fullstack Engineer - Growth strategy - Hook model - how to increase app retention - Incubator - innovation - Iterative and Incremental Development - IT Outsourcing - IT Staff Augmentation - kanban - legacy system - Manual Testing - Market Research Competitive Analysis - Market Research Service - Metaverse - methodology - mobile apps service - Mobile Engineer - Natural Language Processing - NFT - NLP - Offshore Software Development - Offshore Software Development Services - online recruitment - playbooks - Podcast - Product Design - Product Development - Product Development Strategy - Product Owner - Product strategy - product versions - project management - Prototyping early-stage ideas - Quality Software Development - Quantum Computing - Recruitments - recursion vs iteration - refactoring in agile - Remote Work - Research - research problem - Robotics - Sales machine - scalable software - Scrum - Scrum Master - Self-Driving Cars - Serial entrepreneurs - Slash - software - software design - Software Development - Software Development Company - software development team - Software Engineering - Software Product Development Services - solution architect - Spotify Model - Staff Augmentation - Staff Augmentation Services - Staffing Agency in Singapore - teamwork - Tech Talks - tech teams - tech vendor - testing playbook - The Phoenix Project - Unit testing - user interview - user retention design - VB Map podcast - Venture Building - Venture building strategies - Venture Capital - venturecapital - virtual retreat - Web3 - Web and Mobile Apps Service - web app service - Worker Agency Singapore