Up until recently, only tech behemoths and startups had access to AI and machine learning, and the others were kept alluded from this technology. That’s about to change and very soon. The democratization of AI is going to be the new change in 2023, says Gartner. This implies that more organizations will work harder to make AI tools available. AI tools will gather more data as they gain in popularity. That will contribute to the accuracy of AI products.
Additionally, AI will become more affordable, making it accessible to industries that haven’t been able to afford it up until now. Publicly beneficial organizations, public schools, and healthcare facilities could all gain a lot from it. Also, they’ll have a chance to improve their operational efficiency.
In 2023 there are changes being experienced in artificial intelligence technology. Some of these changes are being discussed in this blog post.
Industrialization of AI
AI industrialization, or the movement towards making AI products reusable, scalable. And, to put it simply, accessible to the general public is necessary for AI democratization to succeed. In the ‘Future of Work’ a survey by Pega, 82% of frontline IT staff members express the opinion that more companies involved in AI development will distribute their technologies as low-code solutions. Those who have been developing artificial intelligence (AI) technology for their own gain will become educators. They’ll assist smaller players in utilizing the AI tools that are presently available.
As a result lesser number of businesses will have to start from scratch to develop AI solutions, which will hasten the market’s acceptance of AI.
The pandemic brought attention to the importance of worker safety. That accelerated the robotization trend, which was already evident in several industrial and business sectors. Machines can carry out a variety of activities for people. Such as assisting organizations in increasing productivity and assisting in efforts to maintain social distance. Consider Walmart and Amazon as 2 real life examples. Robots have been used by these organizations to pack and sort products and clean spaces. Chinese hospitals have been deploying robots to measure the temperature of patients entering the complex. And to disinfect the facilities ever since the pandemic began.
Spot, a robot dog designed by Boston Dynamics, is now being used by the police in Singapore to manage street traffic and alert pedestrians on pandemic restrictions. Machines will be used in a variety of market sectors to speed up production. Also, to minimize the
number of personnel who must physically report to work and enable businesses to avoid downtime during lockdowns.
AI in Healthcare
The healthcare sector will also start using Artificial Intelligence and machine learning in 2023. It has already been used by hospitals to better plan their budgets and deliver better care. They have also been undertaking other activities. Machine learning was employed by researchers from Harvard and MIT in 2020 to assess how the pandemic has affected people’s mental health. The algorithms analyzed more than 800,000 Reddit posts to determine if there had been any shifts in the vocabulary and tone of users.
The findings revealed that when compared to the same time last year, the number of threads on anxiety and suicide more than doubled during the lockdown.
According to the researchers, future psychiatrists may benefit from similar analysis to better understand the many types of mental diseases. And how they manifest in patients. Additionally, forum administrators might use it to spot people who might urgently require help. By doing this, they might interact with these individuals and get them in touch with specialists who could help them.
Without a question, technology raises productivity levels in humans. However, it has the potential to entirely replace humans in many situations. According to McKinsey research the deployment of automation would cause up to 375 million individuals to change their occupations by 2030. Do we need to worry that robots will take our jobs? No, not always.
Despite the loss of many jobs, new ones will be created. The experts predict that rising earnings and consumption would result in the creation of up to 365 million additional jobs by the year 2030.
Richer people will spend more money on goods and services. New jobs will be created because of that, both in emerging markets and in the nations that manufacture and deliver them. The demand for experts who can put Artificial Intelligence program into practice. And educate others on how to use it. Will increase as AI becomes more industrialized.
Businesses and governments will pay greater attention to ethics as AI and MI (machine learning) are used more frequently. We have seen numerous instances of AI bias and discrimination during the last ten years. For instance, the American court system has employed the AI system Compas to predict which defendants will likely commit new crimes.
According to the algorithm, black defendants were predicted to have a higher recidivism rate than white defendants. That was false. Due to the original data Compas received the algorithm developed an inaccurate model and was, misclassifying black offenders.
Amazon’s recruiting tool served as another example of how AI has its limitations. In order to assist its hiring team in finding outstanding talent, the company began developing an AI system in 2014. The issue was that the algorithm learned, by using the volume of applications submitted to Amazon over the previous ten years. The majority of which were made by men.
For his reason, the AI program taught itself to favor male candidates while disfavoring female applicants’ resumes.
The Bottom Line
These two real life cases demonstrate the difficulty of developing unbiased algorithms today. Employees, clients, and investors are now expecting businesses to address the ethical concerns with AI. And make the Artificial Intelligence technology transparent and understandable. Companies will also need to consider how much control they want to give algorithms over their operations. Should those algorithms be able to make decisions for people, or should they just give recommendations? Who should be held accountable if a mistake is made? Governments will eventually be forced to enact legislation that will guarantee the accountability and fairness of AI because of this pressure.