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Generative AI Can Automate As Many As 75 Million Jobs Globally; ILO Study Finds
Tech leaders globally have raised concerns about authoritarian governments taking undue advantage of AI tools and the potential for a rise in cyberattacks and disinformation campaigns. Determining whether a generative AI-driven system is accurately gauging human intent, is solving what the customer wants solved, and doing it in a way that aligns with the customer’s values will be an ongoing human task. Customer service personnel will need to be able to evaluate customer interactions in those terms, continually make sure that machine output is aligned with them, and have a means for reporting misalignment. For example, the ability of generative AI to put massive amounts of information at the fingertips of CSRs greatly increases their capacity to resolve the customer’s problem more thoroughly and quickly than either a chatbot alone or a CSR following a rote script. But because conversational AI can sometimes produce plausible sounding but nevertheless incorrect, irrelevant, or nonsensical responses, a human must remain in the loop to ensure the accuracy and trustworthiness of machine-generated suggestions and information.
The four human tasks, unaffected by generative AI and performed entirely by customer service personnel, included such activities as the arrangement of customer-facing environments and directing organizational operations, activities, and procedures. The four customer service tasks that could be fully and effectively automated included such repetitive structured tasks as determining the prices of goods and services and collecting payments. Customer service, a vital activity in almost every industry, provides an instructive case in point of the ways generative AI will enrich — not erase — jobs.
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HubSpot, a leading software marketing company, is seeking an experienced Principal Engineer for their AI Group. The selected candidate will have the opportunity to shape and execute the company’s AI strategy by implementing advanced algorithms and enriching HubSpot’s offerings. Key responsibilities include designing and deploying AI models to enhance user experiences and foster business expansion. This role requires profound AI knowledge, technical leadership, and teamwork skills.
Algorithms underlie an AI’s ability to learn from data, and algorithm engineering requires extensive knowledge of computer science and architecture, data structures, programming, and development. Algorithm Engineers build and fine-tune algorithms for machine learning and AI systems and applications, and while the tools they use will depend on the projects they work on, Java and C++ are used extensively in the field. If you’re still applying to these types of jobs right now, I would take your transferable skills elsewhere and pivot into jobs with more lateral, long-term opportunities and better compensation (Account Manager and Customer Success Manager to name a few). When CoPilot launches, I see companies either having one designated person or a small internal team of Admins in charge of the meeting minutes, memos, phone calls, correspondence, memoranda, status reports, and other written internal documentation. #BizOps managers and Chief of Staffs also fall into this category and are somewhat safe, but I wouldn’t be surprised if their job responsibilities become less administrative and more data-driven and strategic in due time.
Education and Reskilling Are Key
Generative AI may most likely affect legal workers in the US, a recent Goldman Sachs report found. “What took a team of software developers might only take some of them,” he added. The report will be a unique representation of your organization, featuring an “About Me” page and prominently displaying your logo on the front cover.
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.
Because adoption and evolution of the technology will take place almost simultaneously, generative AI will be continually disruptive. But it will also unleash human creativity and empower people to solve problems that were unsolvable before. Imagine, for example, a generative AI system that is continually trained, in part, on customer interactions and uses what it “knows” to suggest previously unimaginable products and services. HR barely wants to hire generalists anymore, but if you want to pivot to another industry or job function, you must be able Yakov Livshits to pivot fast or your application will be placed on the back burner. What I’m trying to say is that unfortunately, if you really want to have a thriving career in a world where many companies are more willing to invest in AI automation products and cheaper labor than you, upskilling should be your #1 go-to job strategy. As DevOps Engineer, you will play a crucial role in building, releasing and operating scalable and trustworthy AI solutions and products that leverage Generative AI to solve business problems in ethical, secure and compliant way.
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You will also participate in all the rituals of Agile methodology and will organise sprint planning, sprint review, retrospective, and more for team members. In this role, you’ll be given the opportunity to build any of these products to meaningfully drive millions of dollars in revenue. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.
As a result, the machine or bot may produce erroneous results or, worse, no results. Emotional intelligence is vital to perceiving, reasoning, understanding, and managing the emotions of oneself and others. Successful leaders and business owners are built on appealing to employee and client emotions. No matter how advanced generative artificial intelligence becomes, it will never have a soul and can never act according to human emotions. It can only do what it’s told and not alter results based on how another party perceives it. Learn how to use ChatGPT for marketing and how to build the prompt engineering skills you’ll need to use AI effectively.
For example, we found that the bulk of work for customer service representatives could be broken down into 13 existing tasks. We then analyzed how the introduction of generative AI might affect each of those tasks. Human, automated, augmented, and emergent tasks — these are the ingredients of a new mix of tasks around which companies should redesign jobs to get the maximum advantage from generative AI. On the positive side, predictions of dire job losses imposed by generative AI may be exaggerated. The report estimates that 4.5 times more jobs will be “influenced” by generative AI compared to those replaced, as seen in the chart above. That’s especially the case in the near term as questions around intellectual property, copyright law, plagiarism, and the limitations of the technology are addressed.