HITL is a mechanism that leverages human interaction to train, fine-tune, or test specific systems such as AI models or machines to get the most accurate results possible. In general, HITL provides following contributions to AI models👩‍💻: Data labelling: People contribute to machine learning's understanding of the world by accurately labelling data. Feedback: With a specific confidence interval, machine learning models forecast cases. Data scientists give feedback to the machine learning model to enhance its performance when the model's confidence falls below a predetermined level.

1. Word of
the Week
www.roadmapit.com
mktg@roadmapit.com +91 413-4207 333
Input raw data
AI Model Processing
Output
AI
Make corrections
Defines outputs
Human-In-The-Loop
Automation
Supervider

2. Word of
the Week
Human-In-The-Loop is an
automation approach that
combines the best of humans and
the best of artificial intelligence to
yield the best results. In simple
terms, HITL is a machine learning
model that combines human
intelligence and artificial
intelligence to build effective ML
models.
www.roadmapit.com
mktg@roadmapit.com +91 413-4207 333

3. Word of
the Week
www.roadmapit.com
mktg@roadmapit.com +91 413-4207 333
Output
Manual Automated HITL Automation
Cost
Reduction
None High
Fast Fast
High
Medium
Medium
Medium
AI & People
Low
AI
90-98% 80-97% 96-99%
Slow
None
People
High
Average
Accuracy
Turnaround
Time
Scalability
Technology
Risk of Errors