AI and the Future Workforce
First, what is AI?
Siri, Apple's voice-activated digital assistant | Editorial Credit: Wachiwit
Simply put, artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. The goals of AI include computer-enhanced learning, reasoning, and perception. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. AI is being used today across different industries from finance to healthcare.
A quick historY
Automation began with the industrial revolution and industrial machinery between 1790 and 1840. Then, like now, people feared the impact of automation on their jobs. However, the industrial revolution actually created employment opportunities.
As early as 1837, Charles Babbage began the creation of a machine he called “The Analytical Engine,” known today as the computer.
Leap ahead to the 1990s, a time for major advances in AI. An artificial intelligence called ‘Deep Blue’ defeated chess grandmaster Garry Kasparov at chess. NASA deployed its first autonomous robotics system, Sojourner, on the surface of Mars. And AI-based data extraction programs became a key part of widespread web use. The 90’s was also when automation meshed with business process management.
In 2011, the release of Apple’s Siri triggered a new age of automation and AI-driven assistants. AI moved away from physical robots and into the development of computerized automation. Business Process Automation (BPA) was becoming more refined and efficient.
Now, automation software is a necessity rather than a luxury. It isn’t perfect, but it’s evolving and improving rapidly by the day.
Jobs at Risk
Here’s a list of ten jobs that could be replaced by AI in the near future.
1. Entry-Level admin roles
Office and administrative support is cited as the job with the highest percentage (46%) of current work tasks that could feasibly be automated and carried out by AI. This shift could lead to a significant transformation in office dynamics and necessitate upskilling for many in administrative roles.
2. Data entry clerks
“Jobs that require decision-making based on data analysis, such as financial analysis and medical diagnosis” are most at risk according to Angelo Sorbello, CEO of AI writing and SEO tool Linkdelta. “In general, any job that involves performing a set of predefined steps or following a strict set of rules is vulnerable to automation,” he explained.
3. Software Engineers & Coders
AI can automate much of the repetitive testing that software engineers currently perform during development, as well as hunting down bugs and patching vulnerabilities.
4. Customer Service Representatives
Companies are now using AI to deal with customer service requests; a lot of small businesses can't afford to employ humans in these roles, so it's becoming commonplace. Jonathan Tian, CEO of CreditYelp, says that AI “has taken over the customer support response” at his company. “Most frequently queried responses are fed to the algorithm to assist our online clients with immediate replies” he added.
5. Legal assistants
AI legal assistants are already commercially available. They will review documents and legal research memos, and help lawyers prepare depositions. They’ll even analyze contracts and revise them if they conflict with compliance laws, as well as identify potential risks your business might face.
6. Copywriting & content production
ChatGPT can produce competent paragraphs of useful, relevant content in seconds – just like a writer or editor can, but quicker. ChatGPT, Jasper and Writesonic are already well-established in the AI universe, charging hefty subscription fees for their premium services.
7. Graphic designers
AI tools like DALL-E can generate images in an instant that compare quite favorably with those done by graphic designers. If technology that can produce unique, original, high-quality images now, what will it be able to do in a year's time?
8. STOCK Traders
With its predictive analytics and real-time data processing, AI can potentially automate and optimize trading decisions, challenging the traditional role of stock traders. “I definitely think it will impact the trading side…people are hired out of college and spend two, three years to work like robots and do Excel modeling — you can get AI to do that in seconds,” according to Pengcheng Shi, Professor of Computing and Information Sciences at the Rochester Institute of Technology.
9. Bankers & accountants
AI's proficiency in handling intricate financial tasks can surpass human capabilities, rendering routine calculations redundant and steering bankers and accountants towards more advisory capacities.
10. Fact-checkers & proofreaders
If Bard or ChatGPT undergoes some fine-tuning and provides sources to every answer it serves up, it could function as a formidable, real-time fact-checker. Proofreading huge texts, which would take an experienced proofreader hours to check, can now be reviewed for mistakes by AI programs in seconds.
The Impact of AI
The fear of job losses due to automation is not a novel concern. Historically, each technological advancement has typically generated more jobs than it eradicated. When automation makes certain tasks more efficient, human expertise is often redirected to areas yet untouched by machines. However, using the past as our compass may be misleading. The game-changer today is AI, a force that doesn't just disrupt one sector but ripples across multiple industries due to its capabilities in language processing, pattern recognition, and problem-solving. Additionally, technology's pace is no longer linear; it's growing exponentially.
In this evolving landscape, roles in programming, robotics, and engineering are on the rise. Yet, there's a catch: those displaced from middle-skilled roles might struggle to transition without intense re-education. Simultaneously, opportunities in low-skilled sectors may stagnate as spending capacities of the middle class diminish. Unaddressed, we're on the brink of heightened unemployment, with associated societal repercussions; less volunteerism, higher crime rates, and drug abuse are all correlated.
The antidote? A comprehensive overhaul of our education system, transitioning away from outdated industrial age models. In the AI era, foundational skills are evolving, and education can't be a one-time event. Continuous learning and re-skilling must become the norm, adjusting to the whirlwind pace of digital transformation.
Amidst this shift, there's hope. Machines, even as they outpace us in many tasks, lack the inherent human touch. They can't decipher our desires or chart our dreams. Humans will always have the unique role of envisioning the future and collaborating with machines to actualize it, ensuring our significance in the tapestry of tomorrow.
Adapting to Change
A broad range of abilities is needed for the creation and application of AI systems. Programming expertise in a variety of languages, as well as familiarity with frameworks and development tools, are requirements for AI experts. Jobs that will be in high demand now and in the near future include:
1. Machine Learning Engineer
One of the most sought-after jobs in AI, these engineers must possess strong software skills, be able to apply predictive models, and utilize natural language processing while working with massive data sets. They must know software development methodology, agile practices, and a complete range of modern software development tools.
2. Robotic Scientist
Their primary function is to build mechanical devices or robots that can perform tasks with commands from humans. Other necessary skills required for this role include writing and manipulating computer programs, collaborating with other specialists, and developing prototypes.
3. Data Scientist
Data scientists collect, analyze, and interpret large amounts of data by using machine learning and predictive analytics to gain insights beyond statistical analysis. They should have expertise in using Big Data platforms and tools.
4. Research Scientist
A research scientist is an expert in multiple disciplines, including machine learning, computational statistics, and applied mathematics.
5. Business Intelligence Developer
In order to analyze complex data and look for current business and market trends, they must be adept in technical and analytical skills, and possess sound communication and problem-solving skills. They are responsible for designing, modeling, building, and maintaining data for complex, extensive, and highly accessible cloud-based data platforms.
6. AI Product Manager
To make sure that AI products and services satisfy corporate objectives and client demands, an AI product manager works with cross-functional teams, including software developers, data scientists, and business stakeholders.
7. Robotics Engineer
An expert who creates, develops, and manages robots and robotic systems will typically conduct market research and customer needs analysis, design and build robotic systems to meet those needs, test and troubleshoot systems, and constantly improve system performance.
8. NLP Engineer
An expert who creates and uses formulas and models to help computers comprehend, decipher, and produce human language is known as an NLP (Natural Language Processing) engineer. An NLP engineer's duties usually include investigating and putting NLP techniques into practice, creating and refining NLP models, and integrating NLP systems into software programs.
9. Research Assistant
A research assistant is typically in charge of gathering and analyzing data, testing new algorithms, and helping to create apps that use AI.
10.Deep Learning Engineer
A deep learning engineer is a specialist in creating and building deep neural networks that can absorb a large amounts of information.
Policy & Ethical Considerations
In the age of advancing AI, we stand at the cusp of transformative change. AI, with its unmatched prowess, brings along opportunities and challenges alike. Ensuring workers adapt and reaping automation's shared benefits require not just acknowledgment but action; a comprehensive policy response is paramount.
Guiding this transition, the White House Office of Science and Technology Policy has outlined five foundational principles for AI's ethical integration. A cornerstone is the creation of "Safe and Effective Systems" where pre-deployment testing ensures public safety. Equally crucial is battling "Algorithmic Discrimination," demanding a vigilant and continuous commitment to equitable system design. Central to upholding individual rights is "Data Privacy" and the right to insight. "Notice and Explanation" further reinforces this by asserting every citizen's right to be informed of and understand how automated systems affect them. Additionally, the principle of "Human Alternatives" emphasizes the importance of personal intervention, offering individuals an opt-out choice and human assistance.
The ethical concerns surrounding AI's meteoric rise are multifaceted. The potential of AI to inadvertently reveal personal information is a significant privacy concern. As we progress with AI integration, the complexities of civil and criminal liability become vital, with AI's actions in the world raising questions of accountability and agency.
Moreover, AI's influence permeates deeper societal veins, affecting labor patterns, taxation, and even politics. It challenges traditional labor norms, potentially altering income dynamics and job landscapes. The tax implications, too, are profound; AI's efficiency might shift fiscal focuses, with possible destabilizing effects. Furthermore, AI's role in politics cannot be understated, whether it's bots influencing narratives or potentially bolstering transparency. The path forward, be it innovation or regulation, demands an equilibrium — embracing AI's potential while safeguarding foundational democratic and ethical principles.
Conclusion
Generative AI is arguably the most gaming-changing technology humans have created in a long time, and an extremely powerful tool for businesses, with significant value in providing invention or breakthrough. But we also need to consider the alternative: AI can also be used against us and cause maximum damage in many different sectors of our society. It completely depends on the creators’ intention of how they want to use AI.
Questions should be addressed: What should be done to ensure AI promotes fairness and inclusion? How can the regulatory system evolve, while not stifling responsible innovation? What can be done to protect privacy and security? Can AI accelerate innovation and growth? What will the workforce of the future look like? How does the United States remain competitive and lead the world in AI? The future will be greatly shaped by decisions made concerning AI.
My best advice for surviving these waves of change? Stay well. Stay informed. Be adaptable.