5 Ways AI Will Impact Application Management

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5 Ways AI Will Transform Application Management

On November 30, 2022, OpenAI (ChatGPT) changed the game for forever in how organizations manage member recognition awards, scholarships, grants, abstracts, fellowships, and so much more.

 

Before this date – organizations relied on short form content and personal storytelling to separate applicants/nominees from raw metrics and from their peers. They were a way for applicants to showcase their unique qualities and personalities – separating them from the thousands of other applicants in the competitive award, grant, scholarship, fellowship, and abstract ecosystem.

 

So what happened on November 30th? OpenAI released an early demo of ChatGPT resulting in the A.I. chatbot going mainstream. Instagram and TikTok were flooded with people recording innovative ways to leverage ChatGPT to streamline tedious tasks such as travel planning, writing computer code, and more. Google search trends went crazy.

 

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Fast forward less than 2 years and mission driven organizations, associations, foundations, and more are now facing challenges never seen before – A.I. generated applications and content. What was once a way to separate qualified applicants from a crowded room of other qualified applicants for limited resources is now a game of cat and mouse to identify authenticity. And while we are 17 months removed from the introduction of ChatGPT – we are only at the precedent of how A.I. will impact organizations in the coming years. This Google search trend looks awfully familiar.

 

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Understanding A.I. and its Current Impact on awards, grants, scholarships, abstracts, fellowships, and so much more.

Artificial Intelligence (A.I.) operates by analyzing large amounts of data and learning from patterns to make decisions or generate content. Applicants frequently use A.I. for writing by inputting prompts or topics, allowing the A.I. to assist in structuring essays/content or solely writing them for the applicant. In recent research amongst scholarship providers, we have identified a significant concern of scholarship essays being written with the assistance of A.I. tools like ChatGPT. This research highlights a growing reliance on A.I. for enhancing the quality of submissions, although there is a crucial distinction to be made between using A.I. as a supportive framework versus having it generate content from scratch. 

So, what does the current state of A.I. utilization look like?

Ok, so award, grant, scholarship, abstract, and fellowship applicants copy and pasting essay prompts into tools such as ChatGPT and using the results as their own work is probably not what organizations are looking for. But in what ways can A.I. be leveraged for good in these highly competitive application based programs?

The 5 Ways AI Will Transform Scholarship Management in 2024

5 ways AI will transform Chamber Awards in 2024

1. Intelligent Automation

Opportunity recommendation and matching

Mission driven organizations manage quite a few competitive submission based programs such as awards, grants, scholarships, fellowships and abstracts that have a wide range of criteria, eligibility, and requirements. Often, applicants may not be aware of the opportunities available to them resulting in underapplied programs or applicants applying for everything, and anything, resulting in wasted time and energy from both the applicant and program provider.

  • Leverage applicant opportunity recommendation and matching tools that based on data provided by the applicant, presents opportunities, categories, awards, scholarships, grants, etc that align.
  • Conduct real-time eligibility and requirement checks bases on content submitted by the applicant.
    • Applicants that are not eligible no longer waste time and energy submitting for an opportunity they are ineligible for.
    • Organizations and program managers are no longer waste time and energy vetting applications that should not be included.
Create a personalized experience

Capturing essential information from applicants equips program managers with the data necessary to create a personalized experience that enhances the applicant experience and strengthens data integrity.

  • When an applicant goes through the opportunity recommendation and matching process we can begin crafting custom questions relevant to the scholarship opportunity.
  • Example: An applicant pursuing a path in surgical oncology may have different application questions, deliverables, deadlines, and review committees than an applicant applying for a career in the arts.
For award programs, create a dual nominator/nominee experience

Leverage a dual process where the nominator starts the submission by inputting who they are, who they are nominating, and why and then let the nominee finish the form by answering more personal questions about themselves. 

  • Nominator and Nominee Information: Start by collecting basic details from the nominator and about the nominee, including names, contacts, and their relationship.
  • Essays and Statements: Include prompts for nominators to explain why the nominee is deserving, focusing on specific achievements or impacts.
  • Supporting Documents: Provide an option for uploading documents like recommendation letters or work samples that substantiate the nomination.
  • Nominee Participation and Confirmation: Implement a system where nominees are notified to complete their part of the form, ensuring a collaborative and thorough nomination process. Confirm submissions via email to both parties.

This streamlined approach focuses on the essential elements while ensuring a comprehensive and collaborative nomination process.

Create a personalized experience for reference collections

Often an afterthought, yet critical to get right, is the collection of references. When an external variable such as references is added to the award nomination application and selection process we must ensure this too follows both proper protocol for data security, but also best practices.

Avoid reference letters:

  • Historically references were collected in a letter format but this is now an outdated and risky method.
  • Letters create a barrier for references.
    • Hard to write
    • Takes time and effort
    • Multi-step to create, write, and send back.
    • Not all references are created equal – some are better written than others, some had more time put into it, etc. Is this a fair representation of the scholarship applicant?
    • Hard to blind PII in a letter.

Leverage reference templates:

  • Outline 3-5 questions that each reference should answer.
  • Lowers the time and effort barrier for references.
  • Creates data consistency amongst all applicants.
  • Creates consistency in the review process with defined data sets.

Use Reviewrs automated reference collection process:

  • Award nominees or nominators will enter the name and email of the reference
  • Triggers an email notification to reference
  • Reference clicks on a link that brings them to a reference template
  • Reference simply fills out the template with the ability to save, log out, and work at their own pace.
  • Visibility to both award program managers as well as to applicants on the progress of references.
  • Actual reference content can be blinded from the applicant.
  • Upon submission, the reference template is automatically attached to the applicant profile.
  • Reference data can be blinded more easily by the review team.
Eligibility screening and qualification

In a world of competitive applications, program managers are looking for ways to narrow down the initial applicant pool to a smaller number for a more indepth and thorough review.

  • Automatically allow candidates to proceed, or not, based on program eligibility. This ensures only those that match the requirement may proceed.
  • Set clear requirements for deliverables and only allow completed applications to proceed that have those deliverables added.
    • Allow candidates to access application information, add deliverables, and return as often as they desire before fully submitting.
    • Once ready to submit, check for completion preventing anyone that is missing a requirement from entering the completed que.
  • Auto-rank candidates based on applicant profile information such as GPA, volunteer hours, etc.

Reviewr’s intelligent automation in action

Intelligent Automation

2. Enhanced Content Creation

While leveraging A.I. to completely write essays or personal stories is advised against – using A.I. to assist with generating content that empowers the applicant be the best version of themselves and position themselves for success is promoted.

Empower creation, not duplication
  • A.I. can be used for Idea generation.
  • Assist candidates in creating the best application content as possible.
  • Create a framework for personalization.
  • Provide spell check, grammar suggestions, and structure.
Lower the barrier – increasing application rates
    • Award, grant, scholarship, abstract, and fellowship applicants WILL utilize A.I. to assist with content creation.
      • Provide a structured and controlled environment.
      • This creates an even playing field for applicants to share the same resources.
      • Increase application rates by eliminating “writers block”.
      • Enhance the quality applications and essays.
Carryover data for multiple opportunities
  • Reduce the redundant nature of applications where things like personal information, grades, etc do not change from one opportunity to another.
  • Carry over applicant data and only require them to submit the unique data requirements for that particular opportunity.
Mock Interviews
  • Personal interviews are going to play a critical role in competitive selection workflows with the rise of A.I. assisted applications. The only way to measure true authenticity is human interaction.
    • Create an environment of success for applicants by providing A.I. driven mock interviews.
    • Tools such as Final Round AI can be leveraged to create interview prompts as well as practice responses that impact follow up questions. Final Round AI: Interview Copilot

 

3. AI and Plagiarism Content Detection

Finally, the elephant in the room. We know applicants WILL use A.I. to assist with their award, grant, scholarship, fellowship, and abstract application content creation. We are also PROMOTING  the usage of A.I. to help generate the framework for a well structured application and essay – so where do we draw the line? How much A.I. is too much? 

Ultimately, this is a decision and question program managers must ask themselves. Here are some themes to consider:

  • Allowing applicants to leverage A.I. to build the framework of a personalized essay is ok.
  • An argument can be made that the applicant’s ability to leverage A.I. and modify prompts to craft a personalized response should be awarded – this is what the future workforce looks like anyways.
  • 100% A.I. generated or plagiarized content is grounds for dismissal.

So, what can we do to better identify the utilization of A.I. generated content and plagiarized material? Reviewr is excited to announce “Sidekick”, an integrated A.I./plagiarism detection tool for awards, grants, scholarships, abstracts, fellowships, and much more powered by Reviewr – the industry leading application management software.

Sidekick is intended to flag applicants for program managers and provide them the resources needed to make data driven decisions.

Detects what percentage of application content is A.I. generated.

    • Detects what percentage of content was plagiarized 
    • Can view what percentage was used on a per-question basis.
    • Organizations can view what is plagiarized and the source it came from 
  • Ex: if the applicant pulled sentences from Wikipedia.com you can see which sentences and the exact article they took the writing from.

See a teaser of “Sidekick” in action.

See Sidekick A.I. in Action

4. Streamline Administrative Workflows

Artificial intelligence streamlines administrative workflows by automating routine tasks and optimizing data management. This enhances efficiency and accuracy, empowering associations, foundations, chambers, credit unions, and more to spend less energy managing, and more energy making an impact.

Auto-group and categorize entries 
  • Leverage intelligent automation to read applications and categorize them.
    • Opportunity
    • Category
    • Award
    • Scholarship
    • Grant
    • Theme
    • Location
    • Much more.
Summarize application content
  • Seamless initial vetting with condensed applications into summarized format. 
  • Create an applicant synopsis to be used to compare to other applicants.
  • From here, narrow the applicant pool to a more manageable number for more in depth review and selection.
  • This should be stated in the proof of process so all applicants know how they are being evaluated.

5. Ensuring a fair, non-biased Selection

At it’s core, Reviewr was developed to not only streamline administrative operational efforts, but more importantly, enhance the experience for both applicants and review teams. This means ensuring each applicant gets the fair change they deserve by eliminating potential bias reviews and unstructured review workflows. Gone are the days of applicants landing in spam and not getting included in the review or being unfairly evaluated based on personal bias.

Matching judges with applicants for evaluation
  • Group applicants based on the judge’s expertise and matched interests with applicants.
  • Randomly distribute applicants to review teams.
    • Ensure compliant review and selection with randomization.
    • Reduce review team workload limits by only allocating a manageable number of of submissions to review.
    • Stay compliant with proof of process.
  • Auto redact personal information from the application from the review teams view to avoid any personal bias.
Tabulate the selection
  • Auto allocate point values to an applicants profile by pulling content from the application form that matches desired scholar requirements.
    • Example, assign point values for hitting specific GPA or volunteer hour thresholds.
  • Seamless online review and selection rubrics.
  • Auto tabulate results eliminating human error and the need for “crunching numbers”.
  • Real-time “leaderboards” track progress and results.
Normalization of results 

Another component of “Sidekick” – Evaluation Normalization.

I love the show Shark Tank and “Mr. Wonderful” is easily my favorite shark. But what if the entrepreneurs pitching their business ideas got judged by different judges than one another? For example, what if I landed Mr. Wonderful but someone else got Barbara? What if the scorecards they used were on a scale of 1-30 and Mr. Wonderful gave me a 19 and Barbara gave someone a 30? What if Mr. Wonderful never gives a 20 – does that make getting a 19 bad? If the show used total and average scores than anyone that Mr. Wonderful scored would naturally be lower in the rankings – is this fair?

Introducing “Evaluation Normalization” This. Is. Big.

  • Did we mention this is big?
  • Reviewr is excited to introduce “Normalized evaluation reporting”
    • Identify judges/reviewers who score on a stricter (or easier) scale than others.
    • Normalize the results to account for a judges particular evaluating habits.
    • Level the playing field for applicants by creating a fair baseline.
    • Identify each judges average score.
    • Set the baseline as 1.
    • If a judge evaluates someone higher than 1, it was better than their average.
    • If a judge evaluates lower than a 1, it was lower than their average score.
    • Take this new normalized average for decision making.
Automated Efficiency

Screenshot 2024 05 07 at 4.39.35 PM 1

Conclusion

“Hey Sidekick, how’d we do”?

Screenshot 2024 05 02 at 1.50.28 PM

Not too shabby. The landscape of award, grant, scholarship, abstract, and fellowship management is rapidly evolving with the integration of AI technologies. As demonstrated, AI brings about transformative changes across various aspects of application management, from intelligent automation to enhanced content creation, plagiarism detection, streamlined administrative workflows, and ensuring fair, non-biased selection processes.

The utilization of AI in application management introduces efficiency and accuracy by automating routine tasks, matching applicants with relevant opportunities, and facilitating personalized experiences. Moreover, AI aids in content creation by empowering applicants to generate high-quality submissions while mitigating the risk of plagiarism through innovative detention methods.

Furthermore, AI-driven systems streamline administrative workflows by categorizing and summarizing applications, ensuring fair evaluations by matching judges with applicants, and normalizing evaluation results to eliminate bias. These advancements not only enhance the efficiency of award, grant, scholarship, abstract, and fellowship management but also uphold fairness and integrity in the selection process.

As we embrace the future of application management in 2024, it becomes evident that AI will continue to play a pivotal role in revolutionizing how awards, grants, scholarships, abstracts, fellowships and more are administered, ensuring equitable opportunities for all deserving applicants while optimizing resource allocation for organizations offering these programs.

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