(EN) Paragraph 1 of this article laid down a general ban on the use of automated decision-making that has legal or similarly significant effects (as mentioned above). This prohibition is intended to serve as a safeguard, ensuring that decisions of this kind are not taken without due consideration and oversight.
This implies that the controller should not undertake the processing described in Article 22(1) unless one of the exceptions listed below applies.
(EN) The use of automated decision-making processes for contractual purposes may be the most appropriate way to achieve the desired outcome in certain situations. This is especially true where routine human involvement is impractical or impossible due to the large volume of data. In such instances, it is essential that the controller is able to demonstrate that the processing is necessary, taking into account whether a less privacy-intrusive method could be employed. For example, if there are alternative methods that are equally effective and less intrusive, then automated decision-making is not considered to be ‘necessary’.
Moreover, automated decision-making may also be necessary for pre-contractual processing in accordance with Article 22(1). It is essential that controllers consider the privacy implications of their automated decision-making processes, ensuring that any processing is necessary and proportionate, and that there are sufficient safeguards in place to protect individuals’ data rights.
For instance, it may be necessary to utilize automated decision-making in order to identify a short list of suitable candidates due to the exceptionally high volume of applications received for this open position. This is done with the intention of entering into a contract with the data subject in order to progress the recruitment process.
(EN) Automated decision-making under 22(2)(b) may be allowed by law, with measures to protect data subject rights. Recital 71 notes potential use for fraud/tax evasion prevention, or service security/reliability.
(EN) Article 22 of the GDPR makes an exception for using explicit consent for significant automated individual decision-making. This is due to the serious privacy risks posed by such processing and, as such, a higher level of individual control over personal data is deemed appropriate.
However, ‘explicit consent’ is not defined in the GDPR. For this reason, the WP29 guidelines on consent (see the “Related” tab for Art.22(2b)) provide important guidance. These guidelines emphasize that consent must be demonstrated through clear affirmative action, such as ticking a box when visiting an internet website or choosing technical settings for an online service.
3. 제2항 (a)호 및 (c)호의 사례의 경우, 컨트롤러는 정보주체의 권리와 자유 및 정당한 이익, 최소한 컨트롤러의 인적 개입을 확보하고 본인의 관점을 피력하며 결정에 대해 이의를 제기할 수 있는 권리를 보호하는 데 적절한 조치를 시행해야 한다.
(EN) According to Art29 Working Party Guidelines on Automated Individual Decision-Making and Profiling for the Purposes of Regulation 2016/679 (2018) the controllers should implement measures that include providing a way for the data subject to obtain human intervention, express their point of view and contest the decision.
Recital 71 further emphasizes the need for transparency around processing, as it outlines that appropriate safeguards should include providing the data subject with specific information and the right to obtain an explanation and to challenge the decision reached after assessment. Furthermore, the controller must provide an easy way for the data subject to exercise these rights, as this ensures they are able to adequately challenge a decision or express their view if they understand how it was made and on what basis.
Errors in data or automated decision-making can lead to wrong classifications and inaccurate projections that can harm individuals. So, controllers should regularly assess their data sets to find any bias, and figure out how to handle any prejudiced elements. Data controllers must regularly review algorithms to ensure accuracy and the absence of bias. Furthermore, they should review the underlying data to guarantee that automated decisions are based on valid and reliable information.
Controllers should establish regular procedures to prevent errors, inaccuracies, and discrimination during both the design and production stages.
The European supervisory authority recommended the following measures in its Guidelines:
Source: http://www.pipc.go.kr/cmt/not/ntc/selectBoardArticle.do?nttId=5969&bbsId=BBSMSTR_000000000121&bbsTyCode=BBST03&bbsAttrbCode=BBSA03&authFlag=Y&pageIndex=6
(EN)
Concern: Request to object to automated decision
Dear Madam, Dear Sir,
I am subject to a decision made by your [company | organization | etc.] based solely on [automated processing | profiling | etc.].
…
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(EN) ISO/IEC 27701, adopted in 2019, added additional ISO/IEC 27002 guidance for PII controllers.
Here is the relevant paragraphs to article 22 GDPR:
7.2.2 Identify lawful basis
Control
The organization should determine, document and comply with the relevant lawful basis for the processing of PII for the identified purposes.
Implementation guidance
Some jurisdictions require the organization to be able to demonstrate that the lawfulness of processing was duly established before the processing.
…
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(71) 정보주체는 온라인 신용신청의 자동 거절이나 인적개입 없이 이루어지는 전자채용 관행 등 자동화 처리에만 근거하여 본인에 관한 개인적인 면을 평가하고 본인에게 법적인 영향 또는 유사하게 중대한 영향을 초래하는 조치를 포함할 수 있는 결정에 따르지 않을 권리를 가진다. 그 처리에는 개인에 관한 개인적인 측면을 평가하는 모든 형태의 개인정보 자동화 처리로 구성된 ‘프로파일링’이 포함되고, 특히 정보주체의 업무능력, 경제적 상황, 건강, 개인의 선호나 관심사, 신뢰성 또는 행동, 위치나 움직임에 관한 측면을 분석 또는 예측하며, 정보주체에게 법적인 영향이나 이에 상응하는 중대한 영향을 미치는 경우 그러하다. 그러나 프로파일링 등 그러한 처리에 근거한 의사결정은 컨트롤러가 적용받는 유럽연합 또는 회원국 법률에서 명시적으로 승인하는 경우 허용되어야 하며, 유럽연합 산하기구 또는 회원국 감독기구의 규정, 기준 및 권고에 따라 실시되는 사기 및 탈세의 감시·예방 목적으로나 컨트롤러가 제공하는 서비스의 보안 및 신뢰성을 보장하기 위해, 또는 정보주체와 컨트롤러 간의 계약 체결이나 이행에 필요하거나 정보주체가 명시적인 동의를 제공하였을 때 등이 이에 해당한다. 어떠한 경우에도, 그러한 처리는 정보주체에게 제공되는 특정 정보, 인적개입을 획득할 권리, 견해를 표현할 권리, 상기 평가 후 내려진 결정에 대한 설명을 얻을 권리, 해당 결정에 이의를 제기할 권리 등 적절한 안전장치를 적용받아야 한다. 그 같은 조치에 아동은 관여되지 않는다.
정보주체와 관련하여 공정하고 투명한 처리를 보장하기 위해서, 컨트롤러는 개인정보가 처리되는 특정 상황과 맥락을 고려하여 프로파일링을 위한 적절한 수학적 또는 통계적 절차를 사용하고, 특히 개인정보를 부정확하게 만드는 요인을 시정하고 오류의 위험을 최소화시키는 데 적절한 기술적 및 관리적 조치를 이행하며, 정보주체의 이익과 권리를 위해 관련된 잠재적 위험을 고려하고 특히 인종이나 민족출신, 정견, 종교나 신념, 노동조합의 가입여부, 유전적 상태나 건강 상태, 또는 성적취향에 근거하여 개인에 미치는 차별을 방지하는 방식 또는 그 같은 효과를 지니는 조치가 이루어지는 방식으로 개인정보를 보호해야 한다. 특별 범주의 개인정보에 근거한 자동 의사결정 및 프로파일링은 특정 조건에 따라서만 허용되어야 한다.
(EN)
Article 29 Working Party, Guidelines on Automated Individual Decision-Making and Profiling for the Purposes of Regulation 2016/679 (2018).
European Commission, Commission Guidance on the application of Union data protection law in the electoral context, A contribution from the European Commission to the Leaders’ meeting in Salzburg on 19-20 September (2018).
EDPB, Guidelines 8/2020 on the targeting of social media users (2020).
European Commission, Guidance on Apps supporting the fight against COVID 19 pandemic in relation to data protection Brussels (2020).
ICO, Data sharing: a code of practice (2020).
Spanish Data Protection Agency (AEPD), Guide on use of cookies (2021).
(EN) The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her. In such cases, the data subject shall have the right to obtain human intervention, to express his or her point of view, to contest the decision and to have it reconsidered.
Scope of the Right
The applicability of this article is limited to automated data processing where the decisions have a big impact on data subjects. According to the Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679, this article sets up a general ban on deciding based just on automated processing, regardless of whether or not the data subject takes any action.
In a nutshell, Article 22 states that:
But, the Article 22(1) ban only counts in certain cases where a decision based just on automated processing, including profiling, has a legal effect on or similarly affects someone. Even in these cases, there are specified exceptions which allow such processing to take place.
Automated Processing
An automated process can produce a recommendation about a data subject. If a person reviews and takes into account other elements to make the final decision, it won’t be a decision that’s just based on automated processing.
The controller can’t bypass Article 22 requirements by making it look like a human is involved. For example, if someone constantly uses automatically generated profiles for individuals without any actual effect on the result, that’s still a decision based solely on automated processing.
To qualify as human involvement, the controller must make sure that any oversight of the decision is significant, not just a formality. It should be done by someone who can override the decision and has the knowledge to consider all the relevant data.
Significant Effect
Even if a decision-making process does not have an effect on people’s legal rights it could still fall within the scope of Article 22 of the GDPR if it produces an effect that is equivalent or similarly significant in its impact. This means that even if there is no legal change, the data subject could still be impacted enough to require the protections under this provision. The GDPR introduces the word ‘similarly’ to the phrase ‘significantly affects’ in order to provide a threshold for significance that is similar to that of a decision producing a legal effect.
A legal effect occurs when a decision based solely on automated processing impacts someone’s legal rights, such as freedom of association, voting, and legal action, or creates legal effects like contract cancellation, entitlement/denial of social benefits, denial of admission to a country of refusal in citizenship.
According to Recital 71, typical examples of other similarly significant effects could include ‘automatic refusal of an online credit application’ or ‘e-recruiting practices without any human intervention’.
For data processing to significantly affect someone the effects of the processing must be great or important enough. This could include decisions that affect someone’s financial circumstances, such as their eligibility for credit; decisions that affect someone’s access to health services; decisions that deny someone an employment opportunity or put them at a serious disadvantage; or decisions that affect someone’s access to education, for example, university admissions.
In many typical cases, the automated decision to present targeted advertising based on profiling will not have a similarly significant effect on individuals. However, it is possible for data profiling to have an effect on individuals depending on the characteristics of the case. This includes the intrusiveness of the profiling process, the expectations and wishes of the individuals, and the knowledge of the vulnerabilities of the data subjects. Even if it has little effect on some individuals, it can have a significant impact on certain groups, such as minority groups or vulnerable adults.
Similarly, automated decision-making that results in differential pricing based on personal data or personal characteristics could also have a significant effect if, for example, prohibitively high prices effectively bar someone from certain goods or services.