The development of artificial intelligence (AI) has accelerated recently, opening up previously unimaginable opportunities to enhance human potential, transform industries, and address pressing global concerns. Notwithstanding these benefits, artificial intelligence raises significant concerns, particularly regarding its sustainability from an ethical and environmental perspective. Society needs to make sustainable AI development a top concern. This ensures we share its benefits and utilize it to combat environmental challenges, and apply it responsibly.
AI holds the potential to drive a positive change in society. For instance, companies like IBM focus on mixing AI with social aims to have big effects on the economy and society. AI helps businesses streamline operations to meet legal rules and use data well. This leads to better results for customers and companies. But achieving these outcomes in a sustainable way requires careful planning, particularly when it comes to data management and resource utilization.
AI has the power to completely transform industries like healthcare. For instance, diabetic retinopathy, a leading cause of blindness that impacts millions of people globally, is challenging to treat due to a shortage of ophthalmologists. It has already been demonstrated that AI models can identify problems just as well as the most skilled ophthalmologists, providing a scalable and durable solution to this problem. In situations like these, artificial intelligence (AI) is not just a possibility; it is the only workable way to successfully solve such pervasive problems.
Deployment and creation of AI requires substantial computing power which requires a lot of energy. AI algorithms and data centers cause much of this problem. Companies like IBM tackled this by making hardware that uses less energy and takes up less space. Their new LinuxONE system lets customers add AI to their current processes in a green way. This tech shows they're serious about being green long-term. It cuts energy use while still working well.
AI is the key in making "smart cities" or clever urban places. Smart cities use resources , reduce energy waste, and give better living. AI is changing city functions, like improving transport and cutting the energy that buildings need. 40% of energy used worldwide is by buildings.
Ethics are super important for AI's future. IBM has always supported playing fair with AI making sure it protects privacy and doesn't pick up bad habits from society. We've seen that data with prejudice can mess up AI. A classic example is the poor treatment of left-handed folks in the past.
AI also helps to open up access to resources and chances for everyone. Large language models (LLMs) have changed how non-native English speakers communicate, letting them express their ideas and join global talks. In the same way, these methods simplify coding allowing even non-tech people to gain programming skills.
Climate change is still one of our biggest problems today, and AI has a special role to play in easing its effects. Take SEEDS (Sustainable Environment and Ecological Development Society) in India, for example. They use AI to study satellite pictures and make maps that help families get ready for climate change. These tools save lives and prove how AI can tackle real issues head-on.
AI is becoming a big deal in our daily lives, and we need to craft it the right way. This requires a sharp eye to prevent AI from magnifying old troubles or whipping up new ethical headaches. Take healthcare AI, which packs a ton of promise. We need to keep tabs on it to dodge abuse and make sure it's available to everyone, including those typically ignored.
To create AI that sticks around different sectors needs to join forces. The battle against "retinopathy of prematurity" is proof that teaming up with pros is crucial for shaping AI that’s sound and makes a difference. Joining hands means AI not solves the techy bits but also gels with what folks hold dear in society.
Given today's neural network architectures have demonstrated that they are successful at scaling, the industry’s attitude has been: why shouldn't we stay the course? But AI scaling laws, which predict continuous performance improvements with increased model size, are beginning to break down as models approach saturation and further gains come at a much larger cost.
We must act now - waiting to hit a barrier is not an option. The brightest minds in industry, academia, venture capital and the government must redirect their attention and resources towards sustainable AI.
In the interests of our world and future generations, it’s time to prioritize efficiency and ingenuity over the brute force scaling of today’s models. This is the only way to unlock the true potential of AI while ensuring this technology benefits all of humanity.