- An outline of automated decision-making
- How automation impacts tax decision-making
- Information about automated decisions
- Effective control of automated decisions
- Technological and legal tools
Why is automated decision-making relevant in the tax domain?
- Taxpayers rely more and more on automated systems for:
- Taxable events: e.g. High Frequency Trading
- Compliance with tax obligations
- States also (could) make use of such technologies:
- Tax authorities: machine learning for oversight
- Judges: tools for handling processes (e.g. the Socrates project)
The decision-making loop
Partial or full automation can change the steps that lead to a decision.
- Human in the loop
- Human on the loop: human override
- Human out of the loop
- Human under the loop: humans conform to automated decisions
Humans and the decision loop
- Even in fully automated systems, humans still play roles
- Designing systems
- Setting up goals
- Those roles might, themselves, lead to responsibility
- So, what does it mean to have a human in the loop?
- Informational: what is going on?
- Supervisory: human intervention
The right to an explanation
- Explanation of what is going on
- Doctrinal construction (law in FR, HU)
- Information must be provided to data subjects
- Model parameters
- How results are produced
- How results are used
- Purpose: allow data subjects to seek redress for harms
Limits and alternatives to explanation
- Challenges to information-rich approaches
- Provided information might not make sense to a non-expert
- Many decisions -> TMI
- Keeping the attention of data subjects
- Alternative constructions
- Impact Assessment and Certification (Edwards & Veale 2017)
- Right to reasonable inferences (Wachter & Mittelstadt 2019)
Intervention in automated decisions
- Possibility of changing outcomes
- Pointwise fix
- Requires effective change
- Legal obligation: e.g. tax authority reserve
- Legal liability
- Correcting errors and biases: e.g. Knight Capital, COMPAS
Automated decision-making in the LGPD
- Data protection law provides new remedies
- Right to review (art. 20, caput)
- Right to clear and adequate information (art. 20, § 1)
- Audits (art. 20, § 2)
- Scope: treatment of personal data
- Does not cover all relevant operations
- Could provide useful analogies and inspiration
for non-personal data
Technology and the human in the loop
- Explainable Artificial Intelligence
- Contestability by Design (see Almada 2019)
- Systems are created with intervention in mind;
- Controls over decisions and interventions.
- Implementation of both approaches can be expensive
Legal controls on automated decision-making
- LGPD remedies as parts of a broader ecosystem
- Limits to judicial and administrative activity
- Ancillary tax obligations
- Technological standards (see ANPD)
- What, then, is the role of intervention?
- Intervention as a dispute resolution tool
- Intervention as the result of dispute resolution
- Automated decision-making may be used by tax autorities, taxpayers,
and judging authorities;
- The use of AIs in decision-making can be relevant for taxation
- New taxable events
- Existing controls may be combined with new techniques
to ensure fair automated decisions.
Decisions based solely on automated data processing
Clear-cut case: automated decision-making
- No humans present in the decision loop
- Automated decision-making, however, should be understood
as a shorthand and not an exhaustive description
- Some decisions can be based solely on
automated data processing even if there are humans involved
Humans based solely on automated data processing
- Example: rubber-stamping (see, e.g. Brkan 2017)
- Algorithm might provide information and choices to a human
- That human decider simply chooses the best-ranked option
- Excluding this sort of decision from the scope of the right
to human intervention would open space for loopholes
A more complicated case
- Instead of rubber-stamping, the human decider now makes a
deliberate choice between scenarios, using their knowledge.
- Is this still a decision based solely on automated
- Yes, if the decider only relies on factual information from the algorithm
- Decider cannot alter the content of a decision: choose your own adventure.
Issues stemming from automated decision-making
- How to detect undesirable effects of automation:
- Harmful decisions: e.g. undue infraction notices
- AI as an enabler of undesirable outcomes: e.g. avoidance
- How to inform stakeholders about relevant decisions
- How to address, preventively or not, decision effects
Who should be held responsible by a decision?
- In the foreseeable future,
it makes no sense to hold machines legally responsible for their actions.
- Not just technical challenges,
but legal ones (Brennan-Marquez & Henderson 2019).
- Even if that were technically possible, AI legal responsibility could be
misused (Bryson et al. 2017)
- Keep a human in the loop.
- Human intervention in automated decision-making.
Requesting human intervention
To request an intervention, data subjects must:
- Know that they are affected by an automated decision
- Know how they are being affected
- Have adequate means for requesting intervention
Design approaches might be used to ensure these goals
Replacing machines with humans
- In many cases, a trustworthy, competent human could probably lead
to better results than automated systems.
- How to avoid a biased or incompentent intervenor?
- Short run: individual liability
- Long run: applying the same standards applied to automated decision
bar applied to automated decisions
Keeping humans informed about automated decisions
- Most modern AI systems are opaque (Burrell 2016):
- Based on models with inherent complexity;
- Technical communication can be difficult;
- Information needed for seeking remedies
- Know that there is a relevant decision
- Know what is going on
Human in the tax loop?
- Current legislation requires a human in the loop only
for decisions affecting data subjects.
- Natural taxpayers might have an effective tool against tax authorities;
- No equivalent duties for intervention against harms to other subjects.
- Taxpayer loops: human as overseer/responsible
- State loops: intervention as a tool for administrative/judicial control
A legal definition of automated decision-making: LGPD
As translated by Ronaldo Lemos et al. (highlights are mine):
The data subject has the right to request for the
review of decisions made solely based on
automated processing of personal data
affecting her/his interests […]
Human intervention in the law
- GDPR Article 22(3) establishes a right to human intervention.
- Brazilian legislation picks a more restricted right to review.
- Limits to ex post intervention;
- Current legislation does not require a human review.
- In both cases, intervention is motivated by a (potential) harm
to the rights and legitimate interests of a data subject.
Is it always desirable to keep a human in/on the loop?
- Keeping a human in/on the loop is crucial
for accountability and quality control.
- However, some tasks would not be feasible with humans: digital economy.
- In other cases, human intervention could be sub-optimal
- Costs involved in bringing a human into the loop
- Human biases and prejudices
- Intervention itself may fail to achieve its desired goals.
Modes of failure for human intervention
- Data subjects might not be able to request intervention
- Lack of information (see Ohm 2018)
- Lack of means
- Intervention failures
- Ineffective intervention
- Harmful intervention
Contestability by design (CbD) and privacy by design (PbD)
- Designing contestable systems cannot be subsumed
into Privacy by Design
- PbD directly protects a value
- CbD establishes an instrument
- CbD may benefit from PbD
- …but they may also clash