Education
Can Data Science Be Completely Replaced by Generative AI?
The rise of AI in the IT industry is a hot topic now. Even data science professionals are now quite worried about their data science career path because generative AI has already started automating their work. Although there is a lot of controversy regarding the replacement of the human workforce by generative AI, a 2013 study by Oxford University has shown that AI could result in the elimination of 47 % of US jobs over the next 20 years.
Due to such data, the rising AI and automation trends like ChatGPT and generative AI tools seem to be a threat to a data science career. But is that true?
In this article, we’ll bust the myth and try to understand the potential of collaborations of data science with AI, better to say, generative AI.
The rise of generative AI in data science
Data science and AI have grown significantly under the technological landscape in the last 7 years. Data science industries used to be run under manual analytical power. But after the AI boom, it is a breaking point. Generative AI models, like GPT 4 have a remarkable capability to mimic human-like text, images, and even code.
Generative AI can provide faster solutions by reducing manual data handling tasks. Due to this reason, professionals have started thinking this can automate every single task of a data scientist. But in actuality, it increases the efficacy of the data preprocessing outcomes.
The emergence of a model like GAN and VAE plays an important role in improving datasets that will help train more aid for data enhancements during the automation of tasks.
If we consider the training of models here, generative AI also stands as a helping hand in browning up the most accurate models. Even regarding data quality assurance, generative AI can help upskill the human effort.
But AI can’t replace human data scientists-
In the above discussion, it’s clear that generative AI is more capable of honing human efficacy rather than initiating core human-like activities.
Though AI has potential it still lacks the rich thinking abilities of humans. For this reason, data scientists are proficient in handling data. To support the pursuit of business objectives, an extremely dynamic data strategy is very important as it supports the acquisition, organization, analysis, and dissemination of information. For the betterment of all these processes, a data scientist needs the skill of effective utilization of generative AI. Let’s dive a bit deeper to dig out why generative AI needs to go long to replace humans.
1. AI suffers from creativity:
Human touch plays a vital role in the handling of data. It’s not merely about breaking down numbers and figures. It’s more than that: creativity is involved in the development of problem-solving and hypothesis generation. It may be missing out on an important creative part in the problem-solving strategies if A-to-Z is done by AI. AI operates within the pattern and algorithm from data and concepts (which are set by humans only), but business requires intuition and emotional intelligence. Only data scientists can fulfill such needs.
2. Lack of contextual understanding:
Generative AI functions from a static algorithm where data scientists bring domain expertise to understanding the nuances of specific problems regarding industries. This contextual understanding is crucial to interpreting the data to make insightful decisions for businesses where AI might fail to land the right decision for businesses.
3. Sometimes, AI finds it hard to interpret complex data
Understanding complex unstructured data needs an in-depth understanding of critical thinking and interpretation. To get the best return from generative AI models, human AI experts need to train the model model accordingly. So, at the initial stage, generative AI itself needs a human expert.
Impact of Generative AI on Data Science in the job market
Generative AI is bringing automation to data processing in all sectors. But it’s now clear that complete replacement of the role of a human data scientist is not at all possible. Though AI can’t eliminate the role of data scientists, it empowers them to do their jobs better.
AI may change roles and specializations in the data sciences field which will lead to new areas of expertise in ethicists, machine learning engineers, artificial models trainers, etc.
In the case where AI will perform tasks automatically, it may have an impact on entry-level data science jobs.
The collaboration of data science and generative AI
What will happen if data scientists hold the hand of generative AI? This trending collaboration will bring dynamic benefits to data science, and here is the list of possibilities.
- Generative AI can assist the data scientist in generating insights from data patterns and the flow of anomaly detection and responses.
- The data scientist can update AI algorithms toward the specific knowledge of technical expertise, the latest trends, and upcoming technology. These will pave the way to derive insights for business intelligence.
- It will foster the data science technique by recommending accurate suggestions for businesses that will aid in augmented decision-making power.
- Generative AI makes work simple to handle repetitive tasks by automation, which saves time and resources.
Are you ready to join the possibilities of data science?
Rising data-driven industries lead to demand for skilled professionals to deliver faster solutions to businesses. So, data science and AI collaboration pave the way for new career potentials. There are plenty of resources online, where you can find one that is right for you. A data science course will facilitate your learning path to achieve your dream job.
Learn data science online under this parameter:
- Proper comprehensive curriculum
- Syllabus coverage
- Hand on projects and industrial mentors
- Data science certification under-recognition of industries
- Interview guidance
In essence, data scientists have to be equipped with AI skills for advancement in the Data Science career path. You need to sign up for a suitable data science certification course online to achieve excellence in data scientist skills.