“AI could aid in eradicating diseases and guide us towards a future with radical abundance.” – Demis Hassabis, CEO, Google DeepMind
The above quote may sound similar to something from a science fiction movie, but it is not. This is a futuristic vision that could soon turn into reality. A while back, Google DeepMind’s CEO Demis Hassabis stated that Artificial Intelligence has yet to revolutionise the healthcare industry and end disease as we know it – but they also believe AI has the capability to usher in a world of radical abundance.
Here at Aixcircle, we explore breakthroughs that are engineering the future, and in this piece, we will highlight this presumed bold claim, along with how AI is changing and enhancing human health, economic frameworks, and the very foundation of civilization.
What Is Radical Abundance?
As mentioned above, Demis speak of radical abundance, or a world that lacks core challenges such as global inequality, hunger, resources, diseases, and any form or type of scarcity through technology.
In historical industrial revolutions, focus was shifted to information, electricity mechanization, however the most recent – AI1 This change revolved around intelligence, automating knowledge, AI optimizes decision making and innovates at a rapid incremental pace.
AI’s potential in the medical field can kickstart us towards this new world and era that Hassabis speaks of.
AI’s Role in Ending Diseases: The Approach By DeepMind
1. AlphaFold: A Milestone in History
DeepMind has developed AlphaFold, an AI system that predicts the 3D structure of proteins with pinpoint accuracy; the learning of which is essential for developing drugs, conducting genetic research, and fighting diseases such as Alzheimer’s, cancer, and COVID-19.
- Old Process: Years of intricate mapping with massive resources.
- With AI: A matter of minutes.
AlphaFold has mapped the structure of over 200 million proteins, practically every protein known to science.
2. AI-Driven Drug Discovery
The speed with which modern-day AI performs tasks has got to the point where advanced algorithms can now identify, simulate, and optimize behavior for the most ideal candidates for drugs and even devise protocols—far outpacing the capabilities of human teams.
- Reduced drug development timelines from 10 years to as little as 2-3.
- Targeting the disease with laser-like precision has become a norm.
- Personalized medication is a newfound option for everyone.
3. Providing Predictive and Preventative Measures for Healthcare
Possessing electronic health records, genomic data, and smart wearables allows AI to do the seemingly impossible:
- Predict diseases before the person even shows any symptoms.
- Deliver limited timeframe preventative measures for chronic conditions.
- Strategically manage resource distribution within hospitals and public health systems.
This results in improved health outcomes coupled with lowered costs and increased average lifespan.
Beyond Abundance Radicle: AI and Medicine
Other than ending ailments, the possibilities Are endless radical abundance across fields may include:
1. Food Security and Agriculture
AI is able to:
- Predict climate or weather impacts.
- Reduce wastage at every level of the supply chain.
- Optimize crops yield.
Efficiently feeding over 9 billion individuals by 2050 may be possible.
2. Environment and Clean Energy
Enabled by AI are:
- Early breakthroughs on battery technology
- Precision emission and pollution counting
- Smarter energy grid systems.
These are crucial in fostering an energy cleaner and efficient world.
3. Extensive Scientific Research
AI is more than capable of:
- Scanning and summarizing piles of literature into digestible content.
- Creating hypotheses such as designing experiments.
- Speeding discovering new elements in Physics, Chemistry, and even space exploration.
This will facilitate every researcher having a boundless amount of aid in the form of AI making them super researchers.
Societal and Ethical Concerns
Having boundless amounts of power means you bear an equally heavy burden of responsibility.
1. Data Privacy
Enabling machines and AI to use sensitive personal and health records may be of technological concern, there are averse reasoning of privacy as well as ethical rules that have to be guarded.
2. Bias and Fairness
Outcomes that do not relate will be met if a machine is trained on socially imbalanced data, In health care AI, testing should be done across varying populations to check equality fairness.
Section 3: Access and Inclusion
In the hands of a select group of corporations or countries, powerful AI tools could result in extreme abundance, yet enable them to gain disproportionate power and wealth. Maintaining equitable opportunities for utilizing these AI technologies cannot be overemphasized.
What Lies Ahead?
Currently, Demis Hassabis’ arguments are grounded in the sheer advancement of science that DeepMind is single-handedly utilizing the power of AI on. And this is not DeepMind’s isolated phenomenon; it is witnessing a rapid inflow of capital from large technology companies, new enterprises, research institutions, and even governments.
