1) The document discusses how AI can be used to improve business decisions by making predictions to help with clinical decision making for things like stroke diagnosis and treatment. 2) It introduces the AI Canvas tool for assessing how employing AI for predictive requirements can improve a business. The tool examines what data and training is needed for predictive algorithms and how outcomes can be used to improve the algorithms. 3) The document emphasizes that using AI requires a mindset change and human-AI collaboration, with the goal of either helping or not harming users.

1. AI, business decisions made simple
The Prediction Requirements #ML
Alexandra Petrus, July 26th, AI-Technologies in Business PT.2

2. @AlxPetrus
/in/alexandrapetrus/
alexandra@bucharest.ai
Alexandra Petruș
Products | Strategy | Emerging tech | AI
Bucharest AI - Initiator & Builder

3. Practice two things in your dealings with AI:
either help or do not harm the user.

4. How to Decide if
Employing AI Improves
Your Business?
AI Assessment
for Prediction-Centered
Requirements

10. Rich video
datasets > AI
solutions to clinical
decision making
Deep Learning
Models for stroke
signatures
identification >
● Improved
diagnosis &
● Reduced time
to respond to
treatment

12. AI Assessment
for Prediction-Centered
Requirements

13. AI Canvas was built by: Ajay Agrawal, Joshua Gans and Avi Goldfarb, Rotman School of Management, University of Toronto.
AI CANVAS
Prediction Judgement Action Outcome
what do you need
to know to make
the decision?
how do you value
different outcomes
and errors?
what are you trying to do? What are your metrics for task success?
Input Training Feedback
What data do you need to run the
predictive algorithm?
What do you need to train the predictive
algorithm?
Have you used the outcomes to improve the algorithm?

14. Mindset change
From deterministic to evolution

15. Expectation out of using AI
Participation of humans and AI-first design

16. Thank you!
Let's connect.