AI-powered tech takes the monotony out of recruiting and hiring candidates

💡 1 CASE STUDY

How AI Assists Recruiters With Daily Operations

Generative AI is transforming how recruiters handle daily business operations. Instead of strictly relying on legacy ATS systems, companies are now connecting their HR and business data to foundational AI models and chat interfaces.

By incorporating AI into daily functions, they aim to boost employee productivity and save time spent completing mundane tasks.

A few examples of how recruiters and hiring managers are utilizing AI models in their operations and processes:

• Automated video interview platforms streamline preliminary screenings, minimizing the time spent on arranging and executing face-to-face interviews.

• AI systems can quickly sift through a large pool of unstructured data aligning candidates with job criteria based on qualifications and experience.

• Use predictive analytics to analyze candidate data, including résumés, social media profiles and online behavior, to predict which candidates are most likely to be successful in the role.

• Candidate facing chatbots can provide immediate help and answer job related questions, eliminating routine tasks and freeing hiring managers to focus on the more creative aspects of the hiring process.

Externally, AI assists recruiters in sourcing deeper levels of data to aid in candidate research. Internally, automation decreases time spent executing on organizational tasks.

Recruiters and hiring managers can focus their time on the aspects of the job that provide the most value; crafting personalized outreach and manage relationships.

🛠️ 2 TOOLS

Plusdocs.com (🔗 link)

Plusdocs is a tool that allows you to quickly create effective presentations by keeping them up-to-date with self-updating Snapshots of your most important data.

ChatPDF.com (🔗 link)

ChatPDF reduces the time spent reading, comprehending, and retaining PDFs. All you do is plug in your document & the app allows you to chat directly with the text.

🥽 3 TRENDS

Canva integrates ChatGPT chatbot to streamline design workflows (🔗 link)

OpenAI just launched a plug-in for ChatGPT Plus subscribers that allows users to communicate directly to Canva.

Users download the element from the OpenAI “plugin store”, prompt a simple description of their desired image, and Canva produces a result. The integration aims to simplify visual content creation, while saving users the hassle of manual conceptualization.

Canvas move to AI-powered design shows a focus on improving user input in the creation process.

Google concludes that AI feedback is more efficient than human feedback in LLM training (🔗 link)

A new study from Google AI compares reinforcement learning from human feedback (RLHF), to feedback from artificial intelligence (RHAIF).

Both RLAIF and RLHF use reinforcement learning to optimize large language models according to human preferences. A major difference between the two is how RLAIF uses a pre-trained AI to label preferences instead of human annotators. RLAIF models allow for training RL models and reduce reliance on human raters.

Findings suggest that RLAIF allows for a more scalable approach by dependency shifting from human to AI.

IBM recently introduced generative AI models and updates to its Watsonx.ai platform. (🔗 link)

IBM is rapidly scaling Watsonx capabilities to serve AI needs and stay relevant in the enterprise.

A few of the key updates include:

• The Granite series model that can summarize, analyze, and generate text

• Watsonx.ai's tuning studio tool now allows customization of models with very small datasets

• Watsonx.data is updated with generative capabilities to discover, augment, and visualize data through a chatbot interface

• Watsonx.governance provides privacy, bias detection, and ethics mechanisms