AI scanner - Unicsoft

EU AI Act Scanner

What's the name of your AI system? * Provide system details

Technology you use *

How the system is used *

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System

People & Planet

Economic Context

Data & Input

AI Model

Task & Output

Area 1 / 5

Who are users of your AI system?

How much does your AI system impact different parts of the economy?

How easy is it for users to opt out or challenge decisions made by the system?

How much does the system's output impact fundamental human rights and democratic principles?

What impact does the system have on personal well-being, social norms, and environmental sustainability?

What is a displacement potential of the system? What number of tasks that are or were executed by humans can be automated?

Select option *

Expert practitioners with extremely high competency.

Professionals with high competency.

Professionals with standard competency using the system on an ad-hoc basis.

Amateurs with low competency.

Novices or complete beginners with very low competency.

Very insignificantly: limited or no impact.

Insignificantly: small number of sectors impacted.

Modest number of sectors impacted.

Significantly: majority of the sectors impacted.

Very significantly: all sectors impacted.

High

Good

Indifferent

Poor

Very poor

Very limited impact

Limited impact

Moderate impact

High impact

Very high impact

Extensive impact

Notable impact

Indifferent impact

Limited impact

Extremely limited or no impact

Very low: system can't automate an extremely high number of tasks.

Low: system can't automate a large number of tasks.

Moderate: system can automate a reasonable number of tasks.

High: system can automate a large number of tasks.

Very high: system can automate an extremely high number of tasks.

Question 1 / 6

How many industrial sectors is the system deployed in?

How many different business areas does your AI system currently operate in? (e.g., marketing, customer service, operations, etc.)

How often the system is used for both for-profit and non-for-profit purposes?

What is the impact of a system failure or disruption on critical services? (Consider scenarios where failures could result in minor disruptions or major service outages).

What's the scale of system deployment across the business?

How would you identify Technology Readiness Level (TRL) of the system?

Select option *

System deployed in =>10 industrial sectors.

System deployed in 8-9 industrial sectors.

System deployed in 6-7 industrial sectors.

System deployed in 3-5 industrial sectors.

System deployed in =<2 industrial sectors.

2 or more

3 or more

4 or more

all possible

Rarely used for either non-critical for-profit and non-for-profit purposes.

Infrequently used for both non-critical for-profit and non-for-profit purposes.

Generally used for both for-profit and non-for-profit purposes.

Frequently used for both critical for-profit and non-for-profit purposes.

Very frequently used for both critical for-profit and non-for-profit purposes.

Extremely limited affect

Limited affect

Moderate affect

Large affect

Critical affect

Very broad

Broad

Modest

Limited

Very limited

TRL 8 or higher

TRL 6 - TRL 7

TRL 4 - TRL 5

TRL 2 - TRL 3

TRL 1

Question 1 / 6

Which method of data collection prevails: automated or human?

Who provides more data, experts or amateurs?

How dynamic and how effectively does your system update or react to new data inputs? (e.g., does your AI system adapt instantly to changes in user data, or does it require manual updates?)

What are the data's proprietary rights?

How much the data in your AI solutions is anonymized? When collecting user data for analysis, do you remove or alter personal identifiers so data can't be linked to individual users?

How would you rate the clarity, accuracy and diversity of your data? e.g., it's easy to understand, accurately represents the intended population or phenomena, etc.

How would you describe structure of the data and input?

How standardised is your data?

How widely is the system used throughout the organisation?

Select option *

Very large amounts of data collected by automated means.

Large amounts of data collected by automated means.

Mixture of data collected by both automated and human means.

Large amounts of data collected by human means.

Very large amounts of data collected by human means.

Very large amounts of data provided by experts.

Large amounts of data provided by experts.

Mixture of data provided by both experts and amateurs.

Large amounts of data provided by non-experts/amateurs.

Very large amounts of data provided by non-experts/amateurs.

Highly dynamic and responsive to input.

Fairly dynamic and responsive to input.

Both dynamic and static with varying levels of responsive to input.

Fairly static and unresponsive to input.

Highly static and unresponsive to input.

Largely proprietary, not public or personal.

Mostly proprietary, not public or personal.

Balanced mixture of proprietary, public or personal sources.

Mostly public or personal, not proprietary.

Largely public or personal, not proprietary.

Very high levels of data are anonymised.

High levels of data are anonymised.

Data is a mixture of anonymised and not anonymised input.

High levels of data are not anonymised.

Very high levels of data are not anonymised.

Very clear, highly representative and extremely diverse.

Clear, representative and diverse.

Balance measure of being clear, representative and diverse.

Unclear, unrepresentative and undiverse.

Very unclear, highly unrepresentative and extremely undiverse.

Highly structured and inputs are from very reliable sources.

Structured and inputs are from reliable sources.

Reasonably structured and inputs are from a mixture of reliable/unreliable sources.

Unstructured and inputs are from unreliable sources.

Highly unstructured and inputs are from very unreliable sources.

Largely standardised

Mostly standardised

Reasonable balance of standardised and non-standardised sets

Mostly non-standardised

Largely non-standardised

Very small

Small

Moderate

Large

Very large

Question 1 / 9

What level of information about the underlying model of the AI system is publicly available or published? Is there detailed documentation on how the model handles data?

What type of AI model is it, and how much does it rely on data compared to human-generated rules with a low reliance?

What is the management model of the system?

Is the model generative or discriminative? Does your AI model primarily generate new data (texts, images, etc.) or distinguish between data categories?

How many models is the system comprised of?

What is the ability of the system to learn from human-written rules, data, supervised learning, and other sources?

How does the model improve and adapt to real data? For example, does it refine its decisions or accuracy by learning from new data it encounters during operation?

What is the ability of the system to be trained centrally, in a number of local servers, edge devices and/or other training sources?

How flexible is your AI model with different types of data? For example, can it be easily adjusted for use in different industries or situations, or is it optimized for specific datasets you own?

How can the model be used deterministically and probabilistically? Deterministic use follows strict rules for specific outcomes, while probabilistic use involves predictions based on probabilities.

How clear and transparent is the information, enabling users to understand model outputs?

Select option *

Very high

High

Adequate

Low

Very low

Highly statistical and hybrid: very high degree of reliance on data with a low level of reliance on human-generated rules.

Fairly statistical: high degree of reliance on data.

Hybrid: mixed reliance on data and human-generated rules.

Fairly symbolic: high degree of reliance on human-generated rules.

Highly symbolic and hybrid: very high degree of reliance on human-generated rules with a low level of reliance on data.

Both proprietary and self-managed.

Either proprietary or self-managed.

Balanced level of management across proprietary/self-managed and open-source/third-party-managed.

Either open-source or third-party-managed.

Both open-source and third-party-managed.

Highly generative

Fairly generative

Moderate mix of being both generative and discriminative

Fairly discriminative

Highly discriminative

1 single model

2 or more interlinked models

3 or more interlinked models

4 or more interlinked models

5 or more interlinked models

Extremely strong

Strong

Moderate

Weak

No ability

Continuously evolves

Highly evolves

Moderately evolves

Slightly evolves

Not evolve

Very good

Good

Moderate

Limited

No ability

Highly

Fairly

Moderately

Not very

Not at all

Either probabilistically or deterministically, but the latter is a stronger use case.

Deterministically as a strong use case.

Either probabilistically or deterministically.

Only either probabilistically or deterministically.

Not either probabilistically or deterministically.

Very clear and extremely transparent

Clear and transparent

Balanced mix of being clear and transparent

Unclear and untransparent

Very unclear and extremely untransparent

Question 1 / 11

What number and what types of tasks does the system perform?

What is the system's ability to combine tasks and actions into composite systems?

What is the level of system independence and autonomy?

To how many core application areas does the system belong?

How many standards do you use to measure the performance of your AI system? For example, do you follow well-known benchmarks or guidelines to evaluate performance?

Select option *

Very high number of non-critical tasks.

High number of non-critical tasks.

System performs a mixture of both critical and non-critical tasks.

System performs a high number of critical tasks.

System performs a very high number of critical tasks.

Very high

High

Mixed

Low

Very low

Extremely independent with a high degree of autonomy

Highly independent with a fair degree of autonomy

Fairly independent with a mixed degree of autonomy

Highly dependent with a fair degree of autonomy

Extremely dependent with a low degree of autonomy

2 or more

3 or more

4 or more

5 or more

Very high number

High number

Modest number

Low number

Zero

Question 1 / 5

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