The case, explained

Algorithmic dismissal and the right to explanation: nullity for software opacity

7 min read · Updated September 2026 · Editorial oversight: Avv. Federico Papa

The evolution of legal debate marks a turning point for digital labor law: legal doctrine proposes the theory of nullity for collective dismissals not for lack of economic cause, but due to the company's inability to explain the decision weights of the AI used to select redundant staff. This perspective brings to fruition the process that began with the first rider disputes, transforming the duty of transparency into a formal validity requirement for termination. The phenomenon stems from the progressive automation of human resource management, in which complex algorithms analyze performance, availability, and feedback. While past litigation focused on the classification of the employment relationship or the discriminatory nature of rankings, current debates center on the evidentiary burden of motivation: if the employer cannot explain why the software selected a specific employee over another, the dismissal is treated as an unmotivated act. We explore this evolution through the twin case of Gaio Sventura and his misplaced trust in technological black boxes.

In brief

The article analyzes the nullity of dismissal resulting from the failure to comply with the right to explanation enshrined in the AI Act and the GDPR. Starting from the Foodinho, Uber Eats, and Deliveroo cases, it examines the employer's obligation to disclose not only the parameters but also the decision weights of the algorithm. Recent theories equate software opacity to a lack of motivation, rendering the dismissal null for violation of mandatory rules on algorithmic transparency.

  1. The fact

    The case arises from the widespread use of automated management systems in the delivery and logistics sectors, as reported by La Stampa and Wired Italia. In the Foodinho case in Palermo (Trib. Palermo ord. 20.6.2023), the court addressed the operation of the Jarvis algorithm, which managed rider shifts. In a separate proceeding pursuant to Article 28 of the Workers' Statute against Uber Eats, also in Palermo, the judge rejected the company's defense based on trade secrets and ordered the disclosure of the ranking criteria. Similarly, the Court of Bologna (order 31.12.2020) had previously censured Deliveroo's Frank algorithm due to its discriminatory impact on workers exercising the right to strike.

  2. The rules at play

    1. EU Regulation 2016/679 (GDPR): Article 22 guarantees the right not to be subject to decisions based solely on automated processing and requires the controller to provide meaningful information about the logic involved.
    2. AI Act (Regulation EU 2024/1689): Article 86 introduces the right to an explanation for decisions taken by high-risk systems, including those used for workforce management, requiring clarity on decision parameters.
    3. Transparency Decree (Legislative Decree 104/2022): Article 1-bis mandates analytical disclosure regarding automated monitoring and decision-making systems, the violation of which compromises the transparency of the relationship.
    4. Law 604/1966: provides that a dismissal lacking motivation or supported only by generic grounds is punishable by nullity or ineffectiveness, as it prevents the worker from exercising the right of defense.
  3. What case law says

    Trial courts, with an emerging orientation, have clarified that trade secrets cannot prevail over the worker's fundamental right to understand the criteria governing their employment and career. Judges have established that the employer bears the burden of translating algorithmic language into clear legal and factual terms, under penalty of the termination's illegality. Furthermore, case law has consolidated the principle that an algorithm failing to distinguish reasons for worker unavailability, such as illness or strike participation, constitutes indirect discrimination. European courts have recently reiterated that algorithmic profiling producing significant legal effects requires a degree of explainability that enables the data subject to challenge the substance of the decision, rather than merely acknowledging its formal existence.

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  5. What it teaches professionals

    1. Preventive Algorithmic Audit: corporate counsel must advise reviewing software procurement contracts to include indemnity clauses and technical disclosure requirements for suppliers.
    2. Documenting Human Intervention: it is essential to establish documentary evidence demonstrating genuine human review of AI outputs, countering allegations of purely automated decision-making.
    3. Analytical Disclosure: a generic contractual clause is insufficient; employers must provide a dynamic disclosure specifying input data and its weight in performance evaluations.
    4. Litigation Management: in court, defense strategy must focus on expert evidence and technical reports translating system logs into factual motivations compliant with Law 604/1966.
  6. Update and rectification note (17 September 2026)

    The previous version of this article incorrectly attributed the Jarvis algorithm to Uber Eats and cited non-existent rulings on the nullity of collective dismissals due to AI opacity, as well as an untraceable case of dismissal for low performance. The text has been corrected to separate the Foodinho case (Trib. Palermo ord. 20.6.2023, Jarvis algorithm) from the Art. 28 proceeding against Uber Eats (Trib. Palermo), and to clarify that the nullity of algorithmic dismissal is currently a doctrinal theory. The overcoming of trade secrets has also been reclassified as an emerging orientation, integrating the correct references, including the Trib. Bologna order 31.12.2020 on Deliveroo.

References: Regolamento UE 2016/679 (GDPR)Regolamento UE 2024/1689 (AI Act)D.Lgs. 104/2022Legge 604/1966Articolo 28 Legge 300/1970Trib. Palermo ord. 20.6.2023Trib. Bologna 31.12.2020

Avv. Federico Papa
Editorial oversight: Avv. Federico Papa·ICAMContent drafted with AI support and subject to editorial source checks. Despite these controls, inaccuracies may remain: reports and rectification requests are welcome. Report a correction

Frequently asked questions

What can I do if I suspect I was fired by an algorithm?

The worker has the right to formally request an explanation of the logic used for the decision. If the company does not provide details on parameters and decision weights, it is possible to challenge the dismissal for lack of motivation and violation of the GDPR.

Can the employer invoke trade secrets to avoid explaining the algorithm?

No, according to an emerging orientation of Italian and European courts, the worker's right to transparency and defense prevails over the protection of trade secrets and software.

Does the AI Act already apply to current dismissals?

The AI Act has entered into force and its provisions on the right to explanation, under Article 86, already integrate the transparency principles that judges use to evaluate the legitimacy of dismissals based on high-risk systems.

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