Emerging AI professions: which one’s the future you?
Emerging AI professions: which one’s the future you?
As AI is spreading beyond tech circles and becoming a household name in the mainstream, more and more people are seriously considering a career in the field. So, let’s look at the most promising and in-demand AI professions hitting the market these days.
AI trainer
What does an AI trainer do?
Imagine teaching a toddler to speak, identify colors, or even choose their favorite cartoon. Now, picture doing something similar, but your “toddler” is actually a computer program. Welcome to the life of an AI trainer!
AI trainers are like the cool “school teachers” of the tech world. Sometimes, they’re even likened to personal trainers from your local gym, coaching machines instead of people. In essence, they help AI systems learn and grow. How? By feeding them tons of information (i.e., training data), such as how to recognize faces in photos or understand human speech.
For example, if you’re teaching an AI solution to identify armadillos in pictures, you’d show it thousands of armadillo photos until it goes, “Aha, got it! That’s an armadillo!” But that’s not the whole story. AI trainers also work with more complex materials. They might teach a virtual assistant (like Alexa or Siri) to respond better to queries or even help self-driving cars understand road signs and traffic rules.
Today, these trainers are rapidly shaping our future by teaching AI the ins and outs of the world. And who knows, they might just be prepping our future robot pals!
What training, skills, and experience are necessary?
Becoming an AI trainer doesn’t require a special magic formula, but there are certain checkpoints you’ll need to hit:
Education
Start with a solid bachelor’s degree, preferably in data management, statistics, or a similar field. Supplement it with courses in AI, machine learning, or computer science.
Skills
Master data-handling skills and annotation tools (i.e., hard skills), as you’ll be swimming in data. Hone your communication talents (i.e., soft skills) that you’ll need to translate human-world quirks into machine-friendly language, often in collaboration with colleagues. Also, be ready to develop basic troubleshooting skills to untangle the occasional AI snags. Familiarity with coding (think Python, Java, or C++) can definitely give you an edge, but it’s not mandatory.
Experience
The best strategy is to seek internships or entry-level positions in the ML field to get real-world exposure. Engage in hands-on projects, even small ones, to apply and build upon your theoretical knowledge.
Bear in mind that not all AI trainers wear the same hat. There are, for instance, model improvers/tweakers who fine-tune AI solutions directly through coding, as well as indirectly through feedback, or conversation designers who focus on making AI’s language interactions more natural. Each one will demand a slightly different subset of skills.
Prompt engineer
What does a prompt engineer do?
Next on the list is prompt engineering, which is sometimes compared to “AI psychotherapy.” This job is relatively new in the field of AI, and it’s tied directly to the emergence of LLMs (Large Language Models). As these sophisticated models have revolutionized how machines understand and generate human-like text, the need for skilled professionals who can guide these systems has skyrocketed.
Why AI psychotherapy, you may ask? Well, much like a therapist trying to unearth deep-seated contexts in a conversation, a prompt engineer deciphers language commands for AI. These specialists craft “prompts,” which are like conversation sparklers, facilitating appropriate AI responses in dialogues. A prompt then is basically a nudge. But it’s not just any random question or statement – it’s a carefully calibrated cue designed to elicit a specific type of answer from a language model.
For example, when you ask an AI for restaurant recommendations, prompt engineers ensure it doesn’t simply spurt out random eateries but instead suggests particular places aligned with your tastes and cravings. So, if you’ve ever marveled at how naturally your AI assistant interacts, save your praise for these savvy tech whisperers!
What training, skills, and experience are necessary?
Every prompt engineer is an engineer, first and foremost. This means you need a comprehensive set of technical skills. However, working with LLMs introduces a unique twist, which means you also need to possess sufficient knowledge of linguistics and NLP (Natural Language Processing).
Education
An undergraduate degree in computer science, software development, computational linguistics, or a related field is fundamental. A postgraduate degree or some coursework in psycholinguistics/cognitive neuroscience can provide invaluable insights into language nuances essential for this role.
Skills
Proficiency in programming is a must. Python is often preferred due to its extensive NLP libraries. Every prompt engineer needs to have a deep understanding of NLP techniques and principles, encompassing both the technical aspects and linguistic intricacies of the field. Strong analytical skills are crucial for designing prompts that evoke targeted responses.
While soft skills are integral to virtually any professional role, a prompt engineer’s focus leans more towards technical expertise / hard skills when compared to positions like AI trainers. Having said that, the ability to communicate complex ideas effectively and work collaboratively remains important.
Experience
Practical experience in an AI development environment, especially dealing with language-related tasks, is highly desirable.
Involvement in projects requiring the calibration of AI responses (such as developing chatbots, virtual assistants, or other interactive AI tools) can distinguish you as a candidate.
Continuous learning and adaptability are very important characteristics in the fast-evolving AI landscape. For newcomers seeking to get their foot in the door, demonstrating this commitment through relevant internships, personal initiatives, and creative problem-solving can make up for limited practical experience.
AI compliance officer
What does an AI compliance officer do?
Often dubbed the “ethical compass” of the tech world, these professionals ensure that AI doesn’t skip the speed bumps of legality and morality. While this is probably the newest and least explored profession on our list, it holds immense potential, as more companies begin to acknowledge the need for this role.
Why “ethical compass”? First, AI compliance officers ensure fairness at the “nursery” stage, examining data sources and waving red flags at any hint of shady inputs or questionable methodologies. Next, they’re also the hawk-eyed monitors of AI behavior “post-deployment,” catching unintentional biases and making sure the tech plays nice and fair in society’s sandbox. Finally, they’re also our privacy sentinels who put virtual seatbelts on AI, upholding strict data confidentiality and other regulatory standards.
For example, if an AI solution is screening job applications, compliance officers see that it doesn’t favor candidates based on ethnicity or gender. They also safeguard the information contained within these applications, ensuring it remains privacy-protected.
What training, skills, and experience are necessary?
Embarking on a career as an AI compliance officer sets you apart in the tech world. Unlike many other roles that demand primarily technical acumen, this position requires a distinctive blend of expertise.
Education
Begin with a bachelor’s degree in law, sociology, auditing, computer science, or a related field. It’s your gateway to understanding the technical and legal frameworks you’ll be working with. It’s also advisable to delve deeper with more specialized courses or a full master’s degree, focusing on responsible AI, ethics, data privacy laws, and compliance standards.
Skills
AI compliance officers must possess a robust set of soft skills in addition to technical prowess. Although coding is generally not a requirement, the ability to perform meta-analyses using specialized tools is essential. Equally important is verbal and written versatility – these professionals operate in the spaces between end-users, AI product managers, and ML engineers, which requires some degree of fluency in the languages of all these domains.
As someone considering this career, you need to develop a keen eye for detail to spot non-compliance and potential ethical breaches. Likewise, you need to enhance your communication skills, because a big chunk of this job is about being able to clearly explain legal and ethical complexities to various tech teams, commercial stakeholders, and government regulators.
Given the role’s emphasis on legality and transparency in [implementing] AI usage, cultivating a strong understanding of ML technology, business standards, and global/regional data privacy laws is vital. Expectedly, problem-solving and critical thinking are key.
Experience
There are two main ways to launch your career here. One is by starting as a compliance officer in another industry (like finance or automotive), leveraging legal expertise, and then moving into AI. Alternatively, you could begin within the AI sector (perhaps in a technical role) and gradually shift to compliance, capitalizing on your hands-on experience.
Whatever your chosen route, it’s always a good idea to engage in projects that involve ethical decision-making or data management. Also, remember that AI compliance is a dynamic field. Stay up-to-date with ongoing legal developments, emerging AI trends, and accountability debates. This role doesn’t just demand expertise – it calls for a passion in the ethical use of technology.