ScheduleBot_PranavJOSHI

Mar 22, 20191 like165 views

The document discusses the inefficiencies of meeting scheduling, noting that Americans waste significant time and resources on meetings daily, costing the US economy billions. It highlights the use of artificial intelligence, specifically scheduling bots, to streamline this process, while addressing challenges related to data requirements and user errors. Microsoft’s approach to developing a scheduling bot, including user feedback and employing humans for microtasks, is outlined as a way to improve the scheduling experience.

Technology

ScheduleBot
L E T ’ S B L O C K C A L E N D A R S
P R A N A V J O S H I

That’s AI
An Artificial
Intelligence to help
you act quickly

That’s AI
too
An Artificial
Intelligence to help
you act quickly

Meetings!! 4
WSJ - Let's Call Off the Meeting and Get Back To Work (2015)
Andy Kessler - https://www.wsj.com/articles/andy-kessler-lets-call-off-the-meeting-and-get-back-to-work-1420156148
Americans
schedule
approximately
11 million
meetings per day

1.5 months
Businesses Waste 4.8
Hours Per Week
Scheduling Meetings
5
https://readwrite.com/2010/10/26/businesses-waste-time-scheduling-meetings/

Time
investment Time needed without
Doodle AI bot
Estimated average
Time needed with
Doodle AI bot
Estimated average
Private Dinner – 4-6 Participants 20-25 minutes 5-10 minutes
Business Meeting – 6-8 Participants 26-30 minutes 13-17 minutes
Private Dinner – 10-15 Participants 90-120 minutes 31-35 minutes
96 people were selected to use Doodle and alternative scheduling tools
https://en.blog.doodle.com/2013/07/08/study-reveals-time-spent-with-scheduling/

Iteration
Iterations
Estimated average
Time needed
Estimated average
Private Dinner – 4-6 Participants 8-12 14-17 minutes
Business Meeting – 6-8 Participants 12-16 20-25 minutes
Private Dinner – 10-15 Participants 10-15 46-50 minutes
96 people were selected to use Doodle and alternative scheduling tools
https://en.blog.doodle.com/2013/07/08/study-reveals-time-spent-with-scheduling/

Calculate
Up to 50% of these
meetings are a waste
of time, costing the US
$37 billion per year
8
https://hbr.org/2016/01/estimate-the-cost-of-a-meeting-with-this-calculator
WSJ - Let's Call Off the Meeting ..Andy Kessler - https://www.wsj.com/articles/andy-kessler-lets-call-off-the-meeting-and-get-back-to-work-1420156148

Challenges in Bot
• Business users have very little tolerance for mistakes
• Good AI needs a lot of data, maximum organisation
don’t have it
• Scheduling scenarios are complex, like one to one, time
zones, venue availabilities etc.
• Who will cover the cost?
https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

A ScheduleBot – Microsoft way
• Start with lo-fi paper prototypes to a group of users to
rapidly collect user feedback
• Next build a wire-frame mock-ups to test them with
users in a slightly more realistic setting
• Wizard of Oz, where UI is real but backend is human
researchers
https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

Microsoft’s Calendar.help
• Learning users expectation from schedulebot
• Help to design workflow with microtasks
• Continue humans-in-the-loop model and hired a staff
of workers to perform microtasks
– One suggest optimal times, another looking at available
locations, and another working to reschedule the meeting
if needed
https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

Microtasks helped to focused worker’s attention on
one thing at a time01
02
03
It helped to collect high-quality data which was used
to automate the scheduling processes
It helped to create variety of machine learning models
to understand natural language

Other ScheduleBots
•X.ai (Amy): $39/month (all prices in USD)
•ClaraLabs.com (Clara): $499/month
•Mimetic.ai (Evie): $25/month (Doesn’t offer custom-domain)

The document discusses the design and implementation of a hybrid-intelligent scheduling assistant, Calendar.help, which utilizes both human and machine intelligence to facilitate meeting scheduling. It highlights the challenges of scheduling, including coordination, complexity, and inefficiencies in existing tools, and details a user-driven approach that integrates human involvement to improve automation and flexibility. Extensive user studies demonstrate the system's effectiveness in successfully scheduling meetings and its impact on workflows within various professional environments.

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ScheduleBot_PranavJOSHI

1. ScheduleBot L E T ’ S B L O C K C A L E N D A R S P R A N A V J O S H I

2. That’s AI An Artificial Intelligence to help you act quickly

3. That’s AI too An Artificial Intelligence to help you act quickly

4. Meetings!! 4 WSJ - Let's Call Off the Meeting and Get Back To Work (2015) Andy Kessler - https://www.wsj.com/articles/andy-kessler-lets-call-off-the-meeting-and-get-back-to-work-1420156148 Americans schedule approximately 11 million meetings per day

5. 1.5 months Businesses Waste 4.8 Hours Per Week Scheduling Meetings 5 https://readwrite.com/2010/10/26/businesses-waste-time-scheduling-meetings/

6. Time investment Time needed without Doodle AI bot Estimated average Time needed with Doodle AI bot Estimated average Private Dinner – 4-6 Participants 20-25 minutes 5-10 minutes Business Meeting – 6-8 Participants 26-30 minutes 13-17 minutes Private Dinner – 10-15 Participants 90-120 minutes 31-35 minutes 96 people were selected to use Doodle and alternative scheduling tools https://en.blog.doodle.com/2013/07/08/study-reveals-time-spent-with-scheduling/

7. Iteration Iterations Estimated average Time needed Estimated average Private Dinner – 4-6 Participants 8-12 14-17 minutes Business Meeting – 6-8 Participants 12-16 20-25 minutes Private Dinner – 10-15 Participants 10-15 46-50 minutes 96 people were selected to use Doodle and alternative scheduling tools https://en.blog.doodle.com/2013/07/08/study-reveals-time-spent-with-scheduling/

8. Calculate Up to 50% of these meetings are a waste of time, costing the US $37 billion per year 8 https://hbr.org/2016/01/estimate-the-cost-of-a-meeting-with-this-calculator WSJ - Let's Call Off the Meeting ..Andy Kessler - https://www.wsj.com/articles/andy-kessler-lets-call-off-the-meeting-and-get-back-to-work-1420156148

9. Can we ask for help?

10. Human vs Machine

11. Challenges in Bot • Business users have very little tolerance for mistakes • Good AI needs a lot of data, maximum organisation don’t have it • Scheduling scenarios are complex, like one to one, time zones, venue availabilities etc. • Who will cover the cost? https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

13. A ScheduleBot – Microsoft way • Start with lo-fi paper prototypes to a group of users to rapidly collect user feedback • Next build a wire-frame mock-ups to test them with users in a slightly more realistic setting • Wizard of Oz, where UI is real but backend is human researchers https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

14. A ScheduleBot – Microsoft way • Selected random users from various companies to signup • Added Virtual Assistant in email Cc on meeting invite • AI suppose to look for schedules and create calendar invites • In reality employees were doing calendar booking • It enable Microsoft to get a product into people’s hands early • Learn deeper understanding of the problem schedulebot may face https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

15. Microsoft’s Calendar.help • Learning users expectation from schedulebot • Help to design workflow with microtasks • Continue humans-in-the-loop model and hired a staff of workers to perform microtasks – One suggest optimal times, another looking at available locations, and another working to reschedule the meeting if needed https://hbr.org/2017/07/how-we-built-a-virtual-scheduling-assistant-at-microsoft

16. Microtasks helped to focused worker’s attention on one thing at a time01 02 03 It helped to collect high-quality data which was used to automate the scheduling processes It helped to create variety of machine learning models to understand natural language

17. Other ScheduleBots •X.ai (Amy): $39/month (all prices in USD) •ClaraLabs.com (Clara): $499/month •Mimetic.ai (Evie): $25/month (Doesn’t offer custom-domain)

20. Thank You P R A N A V J O S H I

Editor's Notes

#3: Image source:- https://pixabay.com/en/architecture-building-business-2179108/
#4: Image source:- https://pixabay.com/en/architecture-building-business-2179108/
#6: Image source:- https://pixabay.com/en/computer-keyboard-apple-laptop-2563737/
#9: Image source:- https://pixabay.com/en/computer-keyboard-apple-laptop-2563737/
#10: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#12: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#13: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#14: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#15: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#16: Image source:- https://pixabay.com/en/coding-programming-working-macbook-924920/
#17: Image source:- https://pixabay.com/en/architecture-building-business-2179108/

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