---
# System prepended metadata

title: 'Responsible Business Decision Making '

---

![Screenshot 2023-11-09 at 16.44.10](https://hackmd.io/_uploads/SJTDCdc7a.png)


# Responsible Business Decision Making 

`collaborations` 

**Author names**: Mishka Nemes, Sarah Nietopski, Vera Matser

:::info
**Key info & logistics**
- Date:
- Venue / delivery mode:
- Audience: business professionals (facilitators)
- Contact name: 
- Contact email: skills@turing.ac.uk
- Reference links:
    - [Responsible AI at Accenture](https://www.accenture.com/gb-en/services/applied-intelligence/ai-ethics-governance)
:::
___
## Why?

### Motivation
**Turing**
- support the goals of the BridgeAI project where the Turing is a delivery partner
- alignment with strategic skills objective focused on AI adoption for SMEs and businees
- grow our portfolio of online courses / resource
- community building opportunity through two-flow contribution of subject matter expertise 

**Accenture**
- `Accenture to fill in`
### Aims and objectives

`Accenture to fill in`
### Guiding principles
- collaborative process for designing, developing and delivery the outputs, engaging our respective communitites from the onset
- open sourced outputs and transparent development process
- outputs are mutually beneficial to our respective communities / target groups
- iterative development process & modular course / learning experience that allows reusing & adapting 
___
## Who?
**Collaboration between Accenture & BridgeAI via Turing**
- engage Accenture's contacts to develop the materials 
- engage the Turing research community to provide input and ideas both at the design & the review stages 
- other?

### Organisers & RACI matrix


| # | Turing | Accenture | BridgeAI |
| -------- | -------- | -------- |-------- |
| Task 1     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |




### Audience

- facilitators or 'Responsible AI champions' working for organisations going through AI adoption in their business development process
    - how do we reach this audience?


Other stakeholders? Delivery teams / partners?
___ 
## How? 
Commission development work with existing suppliers / collaborators, based on a detailed briefing co-designed by the partners.
### Means of delivery
Project work
- work directly with established Accenture former interns/ collaborators (as consultant / developer)

Outputs
- self-paced / blended learning course 
- online toolkit / interactive dashboard
- other?


### Budget & constraints / considerations

- Accenture budget TBC
- Turing Skills resource to be costed in commesurate to person effort in the project
- Christmas period is already too busy on the Turing end
- MVP could take 3 months from January, but full-on project up to 18 months
___
## What?
![diagram](https://hackmd.io/_uploads/rJBO7z04T.jpg)


## User stories
### *Business Professional*

As a business professional ... 
I want to be able to guide my company and evidence that responsible business decisions have been implemented so that we avoid adoption, user acceptance and implementation problems further down the line.

**Acceptance criteria**
[MVP – stage 1]
Professionals **must** be able to…
- View and download the RBDM framework in an editable format
- Follow a self-paced training course that covers:
    - What the RBDM framework is 
    - Essential best practice to use the RBDM framework within an organisation
    - Contextualise the framework within AI adoption phases of an organisation
- Deepen their understanding of the RBDM framework by following a limited set of example case studies 
- Understand the limitations of the RBDM framework both in terms of best practice and current set of incorporated value drivers and consequences and extended consequences.

[Stage 2]
Professionals **should** be able to...
- Interact with a user-friendly read-only version of the webtool
- Attend blended learning session to understand best practice of how to use the framework and learn from interaction with peers
- Access an expanded set of use case in order to learn from others and use them as illustrative examples within the organisation 

[Stage 3]
Professionals **could** be able to...
- Interact with a high-quality user-friendly version of the webtool, including gamification
- Access extended sets of educational materials around the RBDM framework
- Build and save their own project within the RBDM framework tool
- Have a mechanism to contribute curated content back into the RBDM framework

### Educational provider

*As an* education provider 
*I want to* encourage and contribute to responsible business making decisions around AI
*so that* AI solutions are ethically and responsibly designed and implemented and contribute to the public good.

**Acceptance criteria**
[MVP - stage 1]
Education provider **must** be able to
- Course and associated resources in a format that can be uploadable on the Turing OLP (Moodle-based)
- Static file with use cases
- Mechanism to update the materials 

[Stage 2]
Education provider **should** be able to


[Stage 3]
Education provider **could** be able to 

**Defining the MVP**
    - end output: 2-3h *flat* course
    - learning outcomes
        1. Understand and apply the Responsible Business Framework to AI use cases
        2. Identify extended consequences / risks in a variety of AI use-cases
    - format: fully self-paced course
    - what to develop: facilitator guide, videos / recordings, templates (eg use case), slides & reading materials
    - end goal: map the connections between standards value drivers -> responsible business value drivers -> responsible AI value drivers for businesses (adopting or already using AI)
    - Q: can we 

**Improved iterations - Stages 2 & 3**
    - gamified / interactive online learning  
    - sector specific iterations?
    - blended learning delivery
    - feature: map this solution framework to understand drivers & connections between the different consequences (first and second degree)
    

**Learning outcomes** 
`This need more work`



### Deliverables & outputs
1. **Self-paced course** - with possibility of blended / live delivery
2. **Facilitator guide** - builds on an existing one
3. **Use case development** - including template, process and repository to publish and access the use cases
4. **Pilot live delivery of the course** eg with BridgeAI target industry partners

### Milestones and timeline (2024)

| # | When | Who | Notes |
| -------- | -------- | -------- |-------- |
| Map Responsible AI course portfolio     | Text     | Both     |Text     |
| Streamline & secure buy-out between this project and BridgeAI goals and immediate priorities     | Text     | Text     |Text     |
| Review current RBD framework and identify improvement & adaptation leverage points (re-design elements of the solution to ensure responsible use of AI)    | Text     | Accenture     |Text     |
| Review & provide input on the RBD course adaptation to ????     | Text     | Turing     |Text     |
| Identify course developers & secure buy-out     | Text     | Accenture     |Text     |
| Tease out the audiences invited to the pilot delivery     | Text     | Both     |Text     |
| Text     | Text     | Text     |Text     |
| Text     | Text     | Text     |Text     |



___
## Actions
- [ ] Action 1 - assignee X
- [ ] Action 2 - assignee Y
- [ ] etc
___
### Misc Notes
:::spoiler
- add here bullet points for reference
:::