# The framework of the computer-based institution

## The team roles

The [specializations](jobs-specialization.md) of a standard [large-scale enterprise system](cs-distsys-enterprise.md) are severe enough that they need independent roles to do all the work:

First, there is a [natural segmentation into specific domains](jobs-cs-list.md) just to get the computers going:

- [Hardware](cs-hardware.md)
- [Software](cs-software.md)
- [Networking and communication](cs-networks.md)

Then, there's the problem of keeping it [safe](safety.md), which is the domain of [cybersecurity and information assurance](cs-infosec.md).

Of course, at scale things get more complicated, so they need more robust specialty:

- [Database management](database.md)
- [Cloud computing](cs-distsys-cloud.md)
- [Artificial intelligence](cs-ai.md) and [data analytics](data-viz.md)

Since [things need maintenance](https://adequate.life/fix/), there's [IT support and helpdesk](cs-fix.md)

Finally, to deal with the human element including ensuring enough resources and [legal requirements](legal-safety.md), there's [IT governance and management](mgmt-cs.md):

- Chief Information Officer (CIO): makes [decisions](mind-decisions.md) on the group's [purposes](purpose.md)
- More executives are often necessary at more scale:
  - Chief Technology Officer (CTO): makes decisions on *how* to accomplish the CIO's purposes
    - This is an elevation of the Director of Tech Support, with Tech Support Managers and Project Managers under them
  - Chief Security Officer (CSO): makes [cybersecurity policies](cs-infosec-compliance.md)
    - This is an elevation of the Director of Security, with Security Managers under them
  - Chief Artificial Intelligence Officer (CAIO): makes decisions on how to use [AI](cs-ai.md)
  - Chief Data Officer (CDO): makes decisions about the [data](database.md) itself, including [legal compliance](legal-safety.md)

## Risks of worse management

While [bad management](mgmt-badsystems.md) is common, bad CS management is industry-standard due to a confluence of factors:

- A comparatively [younger](maturity.md) demographic than most other industries, which can even lead to [ageism](hardship-discrimination.md)
- A promotion structure based on technical capacity with computers (and therefore fulfilling [the Peter Principle](philosophy-lawsaxioms.md))
- Many of them, as computer nerds, are generally poor on [street smarts](safety-streetsmart.md)

## Ethical issues

One of the most prevalent issues about every decision is that the extreme form of power afforded by [enterprise systems](cs-distsys-enterprise.md) creates an avalanche of interconnected legal issues:

- Algorithmically tailoring [social media](cs-networks-social.md) against some values is a type of censorship, but *not* tailoring it enough is fostering hate speech.
- Collecting data subjects the organization to legal risks (especially when children are involved), but *not* collecting data opens up the opportunities for fraud or defamation.