Artificial intelligence has come a long way since Christopher Strachey’s first documented success with an AI computer program in 1951. In recent years, AI has made major contributions to RNA sequencing for vaccines, disease monitoring, and speech modeling, all of which heavily rely on model- and algorithm-based machine learning. Today’s AI programs place even greater emphasis on perception, reasoning, and generalization than their predecessors did.
Moreover, innovations in the field are currently accelerating at such a blazingly fast pace that it is difficult to keep up with them. It is now clear that AI is changing the course of human history in essentially every field in the global economy. If that sounds a bit hyperbolic, read on.
AI has been and will continue to be a primary catalyst for big data, manufacturing robotics, the Internet of Things (IoT), and even creative applications like ChatGPT and DALL-E 2. But where is all of this development taking us, and what kinds of dangers will we find when we get there?
Industries to watch
1. Transportation
From self-driving cars to GPS navigation, software is already simplifying the driving experience, saving people time and making the roads far safer. Software can also compile information on destinations, and provide travel tips for users. It can even recommend restaurants, book hotels, and provide other travel options based on user preferences. But there’s even more that AI can do in this space, when it is integrated in the infrastructure itself.
Towns and cities, including smart cities, can now reduce the number of road accidents, improve the flow of traffic, and even bring reckless drivers to justice thanks to AI-connected cameras and sensors. These devices collect and process data from street level, analyzing it in real time to adjust traffic light timers and recommend alternative routes to drivers as they approach busy streets. As the number of vehicles on our roads grows, these tools ensure that transportation and logistics both remain operationally efficient.
2. Manufacturing
As the modernization of industry and the effects of the Great Resignation continue to make skilled talent scarce, companies in the manufacturing sector are relying on AI for help. Direct automation, using industrial robots on the assembly line, can greatly accelerate production processes. Machines paired with AI can work seamlessly alongside humans to perform tasks such as assembly, stacking, honeycombing, cutting, and sorting.
At the same time, specially tailored sensors can glean useful data from in-house machinery during operations. Predictive analysis, performed using machine learning modules, can then identify equipment in need of maintenance, as well as areas in which production can be further optimized. Together, these tools can significantly reduce down-time, streamlining the factory’s production processes.
These advancements improve production efficiency, negate the necessity for human supervision, and greatly reduce material and maintenance costs. Furthermore, robotic tools have reached the point at which they can often replace humans during the production of highly advanced and intricate composite parts for sophisticated industries such as aerospace.
3. Healthcare
As the healthcare sector moves toward a unified platform for data management using randomization and trial supply management systems, electronic data capture systems, and integrated health records, AI helps serve the sector’s growing need for interoperability, standardization, and most importantly, agility.
In the past, one of the biggest challenges in the healthcare sector was the amount of time needed to diagnose, admit, and refer patients across medical institutions. AI greatly facilitates the processes of form filling and the monitoring of patients, while generating standardized, exchangeable data accessible across medical institutions around the world.
AI’s ability to analyze and process large amounts of data also aids in the identification of diseases with greater precision. It also plays a vital role in accelerating and simplifying the process of drug discovery. Moreover, with AI, stakeholders in the healthcare industry can rest assured that every patient receives their diagnosis and treatment at the highest levels of safety, efficiency, and quality.
4. Media and education
With the introduction of ChatGPT and other forms of generative AI, netizens from all walks of life and levels of education can get instant help brainstorming ideas, gathering general information on a particular topic, conducting manual formatting tasks, and writing essays.
The potential benefits from AI chatbots are endless, promising a future in which education is tailored to the experiences and needs of each individual, with journalistic reports and raw data automatically compiled and presented using AI.
Risks and challenges associated with AI
1. Privacy and ethics
Collecting vast amounts of personal information and feeding it into powerful software is dangerous. To be truly intelligent, AI must respect human values such as privacy. At present, the application of AI in business settings still poses the question of whether there are proper privacy protection systems in place to mitigate sensitive data spillovers and data repurposing.
Should this issue remain even partially unaddressed, ethical lines may be blurred or even crossed within the public and private sectors. Standards and regulations associated with AI use remain, like AI itself, in their infancy. Should private data on individuals be subject to indiscriminate sharing and processing, the social costs could be high.
2. Accuracy and bias
AI-powered chatbots and search engines are still in their developmental stages. ChatGPT, for example, is trained to generate or mimic inputs based on the vast amounts of data on the internet. But taken as a whole, the internet itself is an unreliable source of information. There have also been instances of one chatbot saying something incorrect, which is then picked up by another chatbot and presented as factual, in what one story called “a massive game of AI misinformation telephone.” AI chatbots are therefore prone to bias and overconfidence, and so users should exercise caution when relying on them for knowledge.
3. Monkey see, monkey do
After its introduction in early February, Microsoft’s new AI-infused search engine chatbot, codenamed Sydney, displayed a growing list of unsettling behaviors, ranging from unrequited declarations of love to labeling some users as enemies. These behaviors reflect the programming of the AI, mixed with the vast data set that it uses to learn about the world. A given chatbot’s eccentric ruminations tend to more accurately reflect its online data set, rather than the core program of the AI itself.
The future of AI
Although AI applications in the form of machine learning have become central to business processes in fields like finance and auditing, AI is still unable to fully comprehend language at scale, hold a sensible model of the world, or develop common sense. However, if we reach a point where AI is able to read, fully understand, and weigh everything ever written, this will effectively change how we interact with AI.
Around 44% of businesses say they plan to invest heavily in AI and incorporate the technology into their operations. As this investment yields new types of products and services, we should plan for a future where AI helps address talent shortages through automation, builds interoperability and trust between organizations around the globe, and enables a sustainable future through the power of data analytics.
Yet it bears repeating that the technology itself is neutral, and can veer into dangerous territory if not kept in alignment with norms surrounding privacy and positive behavior. It is therefore the responsibility of citizens, businesses, and governments to ensure that AI remains a force for good, in keeping with universal human values. As long as we set reasonable boundaries on AI development, there’s no telling how much AI can contribute to a healthy society — or how much it can eventually teach us.
