Generative AI has become the buzzword in the tech world for the past year. There is an ongoing debate about whether this technology is a game-changer or a power tool that can be misused in the wrong hands, to them being the start of the end for all humanity.
Whichever side of the aisle you are on, there is no denying that this technology has immense potential. One area where harnessing its capabilities can be immensely beneficial is Training Management Systems for businesses, specifically for assessments. Let’s explore how.
Generative AI for the Uninitiated
As the name alludes to, Generative AI is a type of artificial intelligence technology that can create or generate new content based on existing content. The content could be in the form of text, images, animations, music, videos, or even code.
AI models are “trained” on vast amounts of data, which then learn from the patterns or structure and then try to replicate them uniquely. For example, Chat GPT, the most famous of them all, uses a Large Language Model (LLM) that was trained on tens of billions of words from the internet.
The exposure to that much textual data has now left it capable enough to have natural human-like conversations, write stories and poems, and even come up with jokes.
This brings us to the core of this blog: how to maximize the benefits of generative AI for assessments.
The Benefits of Using Generative AI for Assessments
The world of corporate training is in constant change of flux. As new technology is developed and the existing ones evolve, so does the need for assessments, a crucial part of any training.
Using generative AI for assessments can give virtual training platforms and L&D professionals a much-needed boost they need to keep up with industry demands for highly qualified employees. Here is how:
1. Create Assessments on the Fly
Creating assessments is no easy task by any means. Let’s use Software Testing as an example here. Creating an assessment that puts a Software Tester’s knowledge to the test is a challenging feat.
The assessment was to be created manually. It would require a tremendous amount of time and brain power to come up with:
- The Test Environment itself.
- Multiple Test scenarios that can mimic real-world scenarios such as stress and load conditions, system errors, predictable ones, and those that are hard nuts to crack and more.
Generative AI, on the other hand, will be able to do the same in a matter of minutes.
2. Personalize Assessments
Personalization is one of the most useful Training Management System features today. AI is already in use to create personalized training content, which has proven highly beneficial in employee engagement and knowledge retention.
However, using generative AI for assessments has the potential to build on the benefits of personalized learning content.
Personalized learning has brought to the surface the errors of the “one size fits all” methodology used to impart knowledge for centuries now. The same holds true for assessment as well.
Each employee has a varied aptitude, skill level, and the amount of experience they carry under their belt. Assessments should take cognizance of the same to test their knowledge accurately.
Using generative AI for assessments will give L&D professionals the ability to generate personal assessments that put each employee’s skill to the test fairly.
Moreover, as generative AI tends to learn over time, assessments, too, can automatically evolve to match the capabilities of the specific employee.
3. Automate Delivery of Assessments
Something even the best corporate training solutions or platforms struggle to get right is delivering assessments at the right time or frequency to keep the momentum of learning going.
While the learning side of corporate training has this functionality dialed down, the assessment side of things can benefit from using generative AI. Quick pop-up assessments can help L&D professionals determine if they need to ramp up their training exercises.
4. Eliminate Human Error and Biases
Generative AI functions purely on the data it is training on. When it comes to assessments, this can play a major role in eliminating all the downsides that come with manual grading of assessments: errors, inconsistencies, and biases.
This improved, and consistent validation of assessments not only brings fairness from the employees’ perspective but also paints a more accurate picture of learning outcomes so that L&D professionals can make better-informed decisions.
Generative AI for Assessments: A Word of Caution
As far as this tech has come, there are still a few points to note when using generative AI for assessments.
1. They are Unpredictable and can be Inaccurate
Generative AI technology can sometimes be unpredictable and tends to spew out incorrect information with surprising confidence. A phenomenon even the companies behind them have not been able to understand fully.
2. They Tend to Develop Biases
Generative AI learns from historical data, and if it detects a bias in it, it also tends to get reflected in its output. Care must be taken to address these concerns before you train the AI for your specific use.
3. The Copyright and Intellectual Property Rights Issue
To use Generative AI for assessments, you have to feed it with specific employee and workplace data. As of today, no robust policy framework is in place regarding confidential enterprise information.
4. The Sustainability Aspect
Sustainability has become a core aspect of business in recent years. Generative AI needs a lot of computing power to function, which works against your organization’s sustainability goals.
The key is using a vendor leveraging renewable energy to the fullest. As futuristic and human-like generative AI is, it still has its flaws.
All things considered, human oversight at all times is key to finding the right balance between reaping all its benefits and managing its flaws.
In corporate training, using generative AI for assessments holds tremendous promise. From better workplace training tests, saving time, and making personalized assessments to automating assessment delivery.
That said, this technology does have its limitations and potential pitfalls. The silver lining, however, is that human oversight and careful usage can help get the best out of this tech.
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