boomerang, the artificial intelligence has become a driving force behind numerous innovations that are re shaping the workplace and enhancing productivity recent breakthroughs, such as open a eyes, touch c, p t, amid journeys a i solutions have demonstrated natural language processing and problem solving capabilities. but at the same time, it has opened a debate surrounding the central risk and safety of a i and i am 50 i and today we're going to be talking about my name's sake artificial intelligence and its impact on the workplace. should we be concerned about it? and what are the limitations of its capability? what used to be purely science fiction is now fast becoming reality with the rise of artificial intelligence platforms. a i adoption in the workplace could lead to

a 40 percent increase in labor productivity by 2035. and companies are increasingly integrating a power virtual assistance like chat g p t in order to streamline customer support operations and implementing chatbox. this allows for quick personalize assistance that is expected to save businesses over $8000000000.00 annually. and even outside of businesses and work processes a i can help automate routine tests and processes at home, freeing up our time to focus on more important things. for example, a i can be used as virtual assistance to automate tests such as scheduling, meeting, sending out inmates, replying to emails, and even creating weekly family tour charts. and as a, i guess, a better understanding human behavior. it can also help us come up with new ideas and find better ways of doing things. for instance,

it can take your habits in your life and preferences to generate ideas for the perfect vacation i temporary or plan a get away. all of these productivity gains will eventually lead to higher profits for businesses and lower prices for consumers. however, this will also be a double edged knife. as goldman sachs predicts that 300000000 jobs could be lost or diminished by this technology. the one particular industry that a has shown right promising is the health care industry, particularly medical imaging analysis algorithms have demonstrated high accuracy in detecting and diagnosing diseases like breast cancer for medical images almost as well. if not better than a double reading by 2 highly trained radiologists, another a, i has actually been trained to work out which sperm are the healthiest and strongest aid and fertility treatments. the average male has barely one intense

firm that are healthy. this a has been taught to identify strong swimmers by their shape and the way that they swim. this technology could mark a significant step forward and the idea of industry by boosting fertilize ation rates and the cost of going through the cycles again and again. a driven analytics have also led to better data driven decision making and businesses and mckenzie report states that a i adoption and data analytics has led to a 50 percent reduction in error rates allow the organizations to make more accurate and impactful decisions. for example, netflix leverage is a i to analyze user data and recommend personalized content contributing to a reported 75 percent of your activity based on a recommendation. the automation has historically created innovation, which needs to new types of jobs being created. many companies will take their cost

savings from a i and use that to grow it's business, ultimately increasing productivity. the growth in a i will likely near the trajectory of past computer and tech product and many jobs in the office. administrative support, legal architecture, engineering, business operations, sales, and health care will be impacted by automation. unfortunately, automation technology has been the primary driver of income inequality over the past 40 years as well. and for more on a i, we are joined by tech expert, an editor of tech for the people dot org, chris garafallo. so chris, can you share with us some specific examples of a i driven analytics that had led to better decision making, resulting in improve business outcomes? certainly, i think we can see that recommendation engines are everywhere. you know, when, whether it's netflix or amazon, you see that, you know,

machine learning and artificial intelligence techniques are being used by all sorts of companies. to recommend products, tv shows, movies even who they want you to be friends with on social media. and that's one of the major ways that most of us will see the use of a i today directly. but we also see it in other industries in farming. for example, farmers are using artificial intelligence to figure out how to optimize their crop yields and how to manage their soil and move crops around from season to season or year to year in order to get the most out of the land that they have. and the resources that they have, we seen your also in driving in the delivery services using machine learning algorithms in a uh, in order to do things like optimize the road that their drivers will take so that we get our packages quicker and they spend less money on gas, for example, when we get to so many industries are using a i right now in a i is

a really broad category of technology. now, what industries can i make a significant impact it? this is a great question because a i is, is a tool like many tools and you can use tools and all sorts of ways. so people have found very creative ways to use a i, for example, the farmer is that again, that are using it to optimize crops. but also, you know, students are using a, i to optimize, you know, how they learn and how they study with flash cards. of businesses or using it to optimize time calendars and their staffing levels. and i think you know, that can also be a certain challenge as well. when you look at how tool h a i is use really when we think about a lot of the, the industries that a, i can impact, it's where there's a lot of data. you know, a huge amount of data that needs to be processed and no person or, you know, traditional computing techniques could actually match the power that the new ai

systems have given us to analyze data, to find patterns and defined ideal outcomes. how do you envision a involving in the future and what potential breakthrough is, do you see that could further revolutionize the workplace? certainly, you know, we need to be able to bring a, i to all people, you know, right? rather than leave it in the hands of a few, just because we all use a i, in our day to day lives now, whether it's machine learning or content generation. you know, when we can actually benefit the entire world. we actually also question, need to question when and how we're going to use it. right now. it's being used primarily to drive profit. it's almost entirely been used by businesses, by universities, by organizations to drive greater profit. and that's where we need to make a change. we actually have to start looking and seeing, you know, is it possible to use a all right, to help make

a better community health care decisions. for example, to identify breakouts of pandemic earlier by analyzing the data from, for example, wastewater. and that's something that has been happening. so there are, there are a lot of ways that we can use these technologies to really build a better future for ourselves. but it comes down to who controls the, is it the wealthy and the bosses, or is it actually the, the, you know, billions of us the global community, who decides that we want to use these technologies, you know, before to, to better all of us. i thought everyone with a basic standard of living, we're already able to access the technology. oh sure you can access to it. you can go and sign up for or chat g p t, for example, or one of the many services that will create an image for you given, you know, just a description of what it is you you want. and that is something that anyone can do on those services are still owned by a small group of people. those are owned by,

by the wealthy. and we don't get to decide the features that they put in. and we don't get to decide how those tools are use, we can play with them and that's effectively, you know, what, in many ways what we're doing when we use something like chat g, p, t. but we don't actually say, you know, get to say that we want to use artificial intelligence systems to figure out better ways to improve the traffic or public transit in our communities, to figure out where pollution is coming from and address it that way. that's the kind of thing that we could use a i for but it doesn't get the funding because it's not profitable. how would you address concerns related to job displacement due to a i adoption and ensure a smooth transition for employees whose roles may be effected. this is such a huge concern, and i think all workers need to be concerned about how their employers are bringing a eye into their fields and their companies. because again, we have very little control. the average person has very little control over how

our bosses or companies are using these technologies. we should be able to say, as workers who know our jobs best, here are the ways that we can use a i hear the ways that we shouldn't or don't want to use it. because ultimately i still stream we far from replacing human intelligence and intuition and creativity . but that's not how those who are seeking only to maximize profit, see it. they just want to make the most money. and if that means they can use a i to replace people and get 80 or 90 percent of the same job done by a machine, they'll do that. so we need to actually guarantee that people have a right to a job and not everyone is going to work in technology. i think that's a, you know, accommodate idea that everyone can learn to code. so to say that's not realistic and it's not for everyone just like not everyone is going to be a farmer or drive

a truck or work in construction. i think there's a lot of different jobs out there that we can, that people do. we need to make sure and across the world that a, i is not used to remove people from jobs, but to actually make jobs safer for people and easier to do, even for the companies to replace workers with a technology and increase their profits. i mean, a recent example is the hollywood strike where the company owners, instead of complying with the strike, is demands are heavily investing on a i instead. yeah, as, as one example we saw recently the during the writers strike on netflix, put out a job posting for an a i engineer. it would make $900000.00 us dollars per year. nearly a $1000000.00 a year between salary and bonuses and stocks. the, for somebody who would work on a, i, for all of the various uses that benevolence uses a eyes for, rather than paying the writers and actors, you know, fair wages. so of course, the,

you know, any time there's a new technology, the bosses, you know, those who are seeking only to make profit are going to go and, you know, try to use that technology to enhance their profit. but that's why, you know, we see, since you brought up the writers straight, the writers are saying like we don't want a, i to replace our work. actors are saying the same thing. there are, there are companies now that will scan your facial patterns and how you react to things in your emotions and your i move mentioned and mouth movements and even your whole body. and then they can actually take you and using a all i call you your likeness, into an image or into a film. and actors are also saying, we don't want that. we don't want our likeness to be able to just be copied like that. and we get no money from it. and so i think we need to listen to the workers who are really being affected by a i what are the writers or actors, teachers,

delivery drivers or anyone else. and really, as we try to understand how we should guide the world in the use of it, as a continues to advance. how do you plan to maintain a balance between a autonomy and human oversight to ensure an ethical and responsible usage? there always has to be oversight and guidance from humans into the use of a a that can't be negotiable. we can't just let a system that has been trained by people. we should say, you know, the, the systems don't train themselves right now. they have to take input from somewhere and we're feeding them that information that they get trained on and that they get learned. and so you can't separate really the autonomy of an ai system from the human oversight because there's always at some point human input into it. whether that's the training or the, you know, internal feedback loops that are involved with it. but there always has to be human

oversight, not just for the development of a i and the, and the deployment of it. also just, you know, whether or not we use it. and then again, that's the question that isn't asked often up is, should we be using a, i think we are a long way on a technical level for having an a i that actually is autonomous. it is not something that is feasible today. it's called artificial general intelligence. ag, i, it's not feasible today. it's not where we're at today. and, you know, the best guess is from the experts, are that we're still very far away from it. that it is not something that we're going to be able to achieve, you know, in the near term. but as we think about, you know, we get there, we really do need to be considering, how is it that we're going to maintain human oversight and who are the humans who are over seeing this a i do we, we cannot just let it go on its own thank you so much, chris, but please stick around. the tech expert,

krista ross will stay with us right after the break. and when we're back, are people concerned about losing their jobs with advancements? is this true? don't go away. the

there's no end in sight over how you're going to continue to destroy the earth. if the case of the med, most of the people i tried to go to the gym, but i'm certainly not ready to fight russia. this is also of soon. this is the 3rd world lunacy re washing press for so the funder line likes to say we have the tools while we just start with stability and business deal. so just let me, let me on have fairly quick propaganda. you know, price here in your i think we don't know the aftermath any time that you're not allowed to ask questions, you should ask all of the questions. the more questions ask the better the answer is will be the

as a continues to advance, there are concerns about job displacements and unemployment. according to the world economic forum, by 2025 automation in a, i could this place around 85000000 jobs. while it makes these operational jobs obsolete, it would also create 97000000 new rules across various industries. however, navigating this transition requires comprehensive workforce development programs. for example, microsoft has invested 20000000000 dollars in an a i for accessibility program to help people with disabilities, acquire new skills and secure employment opportunities in a i driven industries. and in california, the 1st of many labour protests against a is already happening with hollywood writers. wanted to make sure they won't be replaced by a i tools like charge you p t. this will most likely be replicated by unions across

the country. as a technology becomes more prevalent, retail isn't safe either as wendy's is currently testing a drive through chat on. bloomberg estimated that at least a quarter of american workforce will have their jobs impacted by a i in the next 5 years. and if you have to be to work to display software engineers, no single country would be more impacted than india. home to over 5000000 coders, students from the top technology institutes are nervous about a i, because they're the ones who are likely design new ai system. but it's a tens of thousands of other engineers who don't have the degrees from the lea. universities who are worried because of slumped and routine coating jobs is around the corner. it is likely that entry level coating jobs could be all literally rated in the next 5 years in the dangers of unchecked a i. autonomy is another thing to be aware of in the medical field using algorithms

for diagnosing diseases may lead to false positives are missed. diagnosis is not properly supervised. to address this health care professionals need to work in hand them with a i system and leverage the capabilities while exercising human judgments. another major area of concern is a i generate a content which tells me to miss information and fake news. this was a parent in a recent headline when a lawyer used to be to pair of filing for a routine personal injury suit. but the bot delivered fig cases that the attorney then presented to the court. recognizing this organizations like open a i r, emphasizing responsible a i usage. and so for this and more let's bring in again tech expert, an editor of tech for the people dot org, chris graph up. now chris and given that a i can produce contents such as articles and social media posts. how do you

address concerns about the spread of misinformation and fake news generated by a i models? you know, it's not a new problem. there has been misinformation. this information is, you know, fake news. so say for a very long time, well before, you know, you know, the internet or technology, it's, the internet has enabled this kind of information to spread so much faster. it's unable to, to reach millions of people. the 2nd after it's posted and what a i, and particularly content generation, a eyes i have enabled is creating the content a bit faster and having a full news article, rather than just, you know, an e mail for word or a social media post. and so there are websites that are set up with use or full of a i generated fake content. and that is a problem, right? there is a very real problem and it's actually a social problem that we have to solve, not necessarily a technical problem. we need the oversight in the use and development of the art,

but it actually develop, it's actually a social problem that people fall for this misinformation that they don't understand how to verify a new source. and ultimately, even that people don't have basic trust in establishments in governments, in a society that they will fall for, or you know, purposely believe a lot of the content that they see. so that's actually not something we have to address necessarily with technology, but it's really a social problem that we have to address and what are some limitations of a i and what are some jobs that you think i can never replace a will. of course, there's physical jobs a, a isn't going to replace a physical job, somebody, you know, going out and, you know, replacing a power line. for example, you know, robotics didn't get very far, but where we are now and for the foreseeable, foreseeable future, we're not going to be to replace a place where most of these physical, in the real world jobs can be replaced by

a i, a loan. but a lot of the limitations around it come from the ideas that people have about a i, right ai is not one kind of entity or technology. it's many different types of systems and technologies and we will look at it that way. and i mentioned earlier, a g, i artificial general intelligence, and there's a lot of hype right now that we're going to get so close to a g. i. meaning that we need the machines are thinking for themselves. and actually, you know, surpassing human capabilities. we really are nowhere near that, right now. we look at something like chat, g, p t, for example. um, it's very easy to, you know, configurator prompted to spit out nonsense. uh, you know, it answers to a question to have it give you actually, you know, miss information that it's found that the human can actually easily spot. and so there's no real limitations. but the biggest limitation is that again,

we have no say really over how these technologies are being used with the potential for a i to mimic human language and voices. how can we prevent a i systems from be exploited for malicious purposes, such as social engineering or fraud? yeah, so there does need to be regulation on these kinds of things to make it to make it illegal, to use, you know, deep fakes to make fake phone calls for example, which is a, something that's happening now. the people are scanning the voices of people and calling their relatives and using ai to have whole conversation to scan them out of money. for example, that needs to be illegal to create or use that kind of product. but again, it also goes back to this idea that it's not just a technology problem, but there's a social problem that leads to crime in general, any kind of crime, any kind of, you know, scamming and these social problems also have to be addressed. where, you know,

why is it that people are driven into scam other people or to commit crimes, whether it's using a gun on the street or using an artificial intelligence from a computer or half way around the world. you know, we need to be able to address things like poverty and, you know, decide of dissatisfaction with society and the general alien nation that so many people feel the lack of hope they feel to, to prevent a lot of these things. but like i said, we do have to actually address and make it legal. the use of these technologies as well. certainly raise the barrier of entry for a i such as maybe the price of a i. so people are not tempted to commit fraud, but this would limit access of the technology to select as you know. absolutely, i think what i mean instead, you know, not just the, we're not raising the price of for the, you know, limiting access to a are in that way. but, you know, she actually limits the limit poverty,

which is the number one reason people commit crimes, especially property crimes, is because they have a need, they need to have money, they need no money for their rent or food or medical care. and that's actually number one reason some people commit these kinds of crimes, especially international that you, when the, when the crimes cross international borders. and so we have to address the issues of poverty that lead to people doing these things. it's similar to the e mail scans that i'm sure we all get, you know, saying that you've won a lottery or something like that. you know, nowadays they end up our spam folder. but and those have nothing to do with a i, but they still show that there is a entire industry built around that and people buy into it because they feel that they feel a need to make that money. however they can. thank you so much, chris, for all your time today. a i as a general term these days. and these previous examples are in reality, not real a i, but a combination of big data and machine learning. true a,

i has not yet been achieved. and instead, these systems are designed to excel at specific tasks, but lack broader cognitive abilities. the future of true a, i would be a system that possesses general cognitive ability, similar to human intelligence, enabling it to be use and learn and understand various tasks rather than to just be girl to take what a hears and sees online. while this tool would be a great tool, it could also be used for harm spreading this information and manipulation with the rise of tried to be suddenly some of the most respected scientist in the field are speeding up their own timelines for when they think computers learned to out think humans and become manipulative. a still many do not believe in a i take over something that people need to be concerned about right now. the ripple effects of the technology are still very unclear and entire industries are bracing for disruption, including what used to be considered

a stable white color job like a lawyer or physician. i'm christy. i. thanks for watching. and we'll see you right back here next time on the cost of everything. the take a fresh look around his life kaleidoscopic isn't just a shifted reality distortion by powell of tired vision with no real opinions. fixtures designed to simplify will confuse who really wants a better wills, and is it just as a chosen few fractured images presented as 1st? can you see through their illusion going underground can the same rom

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