How much do you know about how your company uses AI? If you’re like most employees, you probably don’t have a clue. According to a survey by UKG Solutions, a human resources and workforce technology company, more than half of workers (54%) are in the dark about their employers’ AI practices. And that’s not the only gap. While 78% of C-suite leaders say they use AI in their organizations, 68% of them confess to making AI decisions that may harm their employees.
But it’s not all doom and gloom. Executives see AI as a tool, not a threat, and estimate that 56% of their staff already use AI to enhance or automate their job tasks. And workers are eager to learn more, with 75% of them saying they would be more excited about AI if their company was transparent about it. As AI becomes more widespread, with companies expecting that 70% of their workforce will use AI for job tasks by 2028, they also need to take responsibility for creating ethical and sustainable AI policies and investing in upskilling their employees.
It is natural to feel afraid of what this would mean for many of our professions. Many of us entered the labor market long after the establishment of the internet, making this the first time we see a technological disruption of this degree. Some professions (data entry, telemarketer, travel agent, bank teller, business and data analyst, financial manager, accountant) may see a decline in opportunities as AI technologies improve and become more widespread.
However, it's not all bad news. The rise of AI is also creating a demand for workers who can understand, develop, and manage these technologies. This includes not only tech roles, but also roles in ethics, law, and business strategy that are focused on managing the impacts of AI.
For college students and job seekers looking to capitalize on this trend, developing skills in AI and data science could be a wise move. This might involve studying computer science, statistics, or a related field, and gaining practical experience through internships or projects.
Additionally, soft skills like problem-solving, adaptability, and a commitment to lifelong learning are also important, as the nature of these roles and the technologies they involve are continually evolving.
In essence, while AI poses certain risks to the job market, it also offers many opportunities for those who are willing and able to adapt and upskill.
The advent of AI technology today can be compared to the rise of the internet in the late 1990s and early 2000s, where the internet opened new avenues for business and communication, like how AI is creating new opportunities today. The internet era saw the creation of jobs that never existed before, such as web developers, digital marketers, and e-commerce specialists.
However, with the rise of the internet, many traditional businesses that failed to adapt to the digital age struggled to compete, leading to job losses. Similarly, AI's ability to automate routine tasks, execute simple transactions, and certain types of analysis much faster than humans threatens to reduce, or eliminate altogether, a broad range of professions.
Those who adapted their skills to the new era of the internet often found new, more fulfilling roles and opportunities. They were able to capitalize on the growth of digital industries and create successful careers. For example, many graphic designers learned web design, and salespersons transitioned into digital marketing roles.
On the other hand, those who failed to adapt faced lingering challenges. Many traditional jobs became obsolete, and without the necessary digital skills, finding new employment became more difficult. However, it's important to note that many also found new opportunities in industries that remained less affected by the digital revolution.
The same pattern is likely to repeat with AI. Those who embrace the change and upskill for the new job landscape will likely find new opportunities and have successful careers. On the other hand, those who resist the change may see their jobs become obsolete and may struggle to find new employment.
In both eras, the key to navigating these shifts has been adaptability and a commitment to lifelong learning. As AI continues to evolve and reshape the job market, these qualities will become even more essential.
For those interested in learning more about AI integration into the workplace, there are free resources and courses available.
•Google's AI Hub: Google offers free resources and tools for learning AI and machine learning. Their crash course on machine learning is particularly useful for beginners.
•Coursera: This platform offers courses like "AI For Everyone" and "Machine Learning" by Andrew Ng. These courses provide a comprehensive introduction to the basics of AI and machine learning.
•MIT OpenCourseWare: MIT provides free lecture notes, exams, and videos without any required registration. The "Artificial Intelligence" course is a great place to start.
•IBM's AI Fundamentals Program: IBM offers a free 10-hour course to train you in AI fundamentals. This program is designed to help anyone without a technical background understand AI, machine learning, and robotic process automation.
•Amazon's AI Courses: Amazon provides an excellent overview for managers, decision-makers, and those curious about AI.
•Introduction to Artificial Intelligence: This brief introductory course explains what AI is, its importance, and its relationship with machine learning and deep learning.
•Generative AI for Executives: This collection of free, brief, and easy-to-follow videos is designed to help C-suite executives understand how generative AI can address their business challenges and spur business growth.
The free resources listed below are more technically oriented and may be most beneficial for coders, developers, or those specifically interested in machine learning:
•edX: Another learning platform that offers various AI and data science courses, including professional certificate programs.
•Fast.ai: This organization offers a free course called "Practical Deep Learning for Coders" which is great for those who want to dive deeper into the practical aspects of AI.
•Machine Learning University (MLU): Amazon’s learn-at-your-own-pace MLU Accelerator learning series is designed to kick-start your machine learning journey with foundational courses on Natural Language Processing, Tabular Data, and Computer Vision. They also offer an advanced five-day lecture series on tree-based and ensemble models after completing the Accelerator Series. The courses include sequential YouTube videos taught by Amazon scientists, hands-on practical examples, Jupyter notebooks, and slide decks, providing a comprehensive self-service pathway to understanding the foundations of machine learning. All course materials are available on GitHub.
Khan Academy: Offers courses like "Intro to JS: Drawing & Animation" and "Intro to HTML/CSS: Making webpages" that can be useful for understanding the basics of coding, which is essential when delving into AI.
Remember, gaining skills in AI and related fields is not just about understanding the technology. It's also about understanding how to apply this technology to real-world problems and ethical considerations. So, take advantage of these resources and start your journey into the world of AI.
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