Not long ago, we talked about artificial intelligence as the technology of the future, but now with the launch of chatbots (ChatGPT) in 2022, November 2009, it has become an integral part of our daily lives, whether at work or for personal use. ; A defining moment in AI and its accessibility for all.
And because AI is able to quickly analyze large amounts of data; Whether it is answering customer questions, analyzing and predicting weather trends, or designing advertisements, it is a very useful tool for decision-making in various industries.
However, there are studies that warn of potential dangers. A recent study from the University of Cambridge's Center for Existential Risk Research shows that despite its huge potential, AI can pose risks to privacy, bias, inequality, and security.
As this controversy continues, AI advances rapidly, continuing to analyze vast amounts of data beyond human reach, saving time, money, and even lives.
Here are 4 ways AI helps people make better and faster decisions:
1- Extinguishing forest fires:
The World Meteorological Organization projects that climate change will lead to a 30% increase in the number of severe fires by 2050 and 50% by 2100.
As a result, in 2022 the World Economic Forum launched an initiative called FireAld to develop smart solutions that can predict the likely location and severity of wildfires, and how best to fight them.
One of the main issues is the inconsistency in reporting local weather data, and the forum called on public authorities to work together to ensure that AI tools have the best data to accurately predict wildfires.
2- Targeting the right customers:
Bringing the right customers into the market to make a purchase is critical to the continued growth of your business during challenging economic times. Companies worldwide will spend more than $567 billion on digital advertising in 2022.
Research conducted by Deloitte has found that AI can have a significant impact on advertising by identifying which channels people prefer to contact and creating personalized messages for potential customers.
The American Marketing Association is also using the platform (Rasa.io) to create a personalized newsletter for each of its 100,000 subscribers, and has found that AI can help increase readership, give brands deep insights and give agencies time.
And in a case study (conducted by the American Marketing Association) on the use of artificial intelligence in content marketing; The Adobe Drift Conversation chatbot, which has raised more than $10 million, is shown to interact with site visitors in natural language at every step of the visitor's journey; The bot is able to quickly direct visitors to what they need and, if there is no response, transfer the conversation to a human.
3- Helping firefighters see through smoke:
When the firefighters reached the burning building, it was difficult for them to determine exactly where they had gone. Portable thermal imaging cameras have limited capabilities, but in 2022 the Scottish Fire and Rescue Service introduced an AI-based system that could help firefighters quickly locate stranded people.
Using radar and motion sensors, as well as thermal imaging cameras, the helmet-mounted device can provide a clear picture of the interior of a burning building, allowing firefighters to quickly locate victims and their colleagues.
AI also plays a role in helping people after natural disasters such as fires and floods, as Swiss Re has developed an AI-based tool that quickly analyzes drone footage of damaged properties to help guide decisions. Faster - quickly.
4- Rapid detection of diseases:
The impact of AI on health is enormous and it is being used to support areas such as diagnosis, clinical decision-making, monitoring, treatment and workflow. AI-assisted medical imaging is already in use, and several pharmaceutical companies are investigating how AI can be used to develop drugs.
By 2026, two-thirds of medical imaging operations are expected to use artificial intelligence to detect diseases and guide treatment. Microsoft is developing machine learning models that use hospital data to automatically highlight tumors and healthy organs in patient exams. The decision is made by the oncologist. Effective in treating cancer and providing a more personalized service to patients.