Legislating Algorithmic Choice Against Big Tech Revenue Drivers

The Albanese government's proposed digital duty of care laws change how we regulate online spaces. By requiring platforms to offer an off switch for algorithms, the government wants to shift users from passive consumption to active control. This reveals a tension: the engagement metrics that drive Big Tech business models are the same mechanisms linked to user harm. For leaders and observers, this is a case study in how legislation forces firms to choose between their primary revenue drivers and public safety. Understanding this dynamic is necessary for anyone tracking digital policy, as the outcome will set the precedent for how governments globally attempt to constrain algorithmic influence.

The algorithmic engagement trap

The core conflict lies in the misalignment between platform incentives and user well-being. Algorithms maximize engagement, often by funneling users into doom scroll rabbit holes. When educators like Chanel Contos argue that these systems expose young people to violent or misogynistic content, they point to a structural feature of the business model rather than just poor moderation.

"The algorithm is the process that big tech uses to decide basically what you see on your social media feed. And for a while now some experts have been raising the alarm that they might be doing more harm than good because of the harmful content they can expose Ozzie's to."

-- Squiz Today Transcript

The government's proposed pop-up solution, which forces platforms to offer a chronological feed option, attempts to break this feedback loop. However, the system is designed to route around such friction. Because Big Tech relies on high engagement to maintain its value, any move that reduces time on site hits the bottom line. We should expect platforms to comply with the letter of the law while potentially making the opt-out experience cumbersome, keeping the majority of users within the algorithmic loop.

The legislative tug-of-war

The success of these laws depends on a political balancing act. The government faces pressure from those who believe the current draft does not go far enough, such as the Greens who favor an opt-in by default system, and those skeptical of government overreach, such as the Coalition who fear censorship.

This creates a high-stakes environment where a middle-ground solution, like a notification, might satisfy the requirement for action without changing the underlying systemic problem. If the legislation passes in its current form, the real-world impact will depend on how strictly the $100 million fines are enforced. If the cost of non-compliance is lower than the revenue generated by algorithmic engagement, the system will treat the fines as a cost of doing business.

Mapping downstream consequences

When we look at systemic changes, we must look at how the actors respond. If Australia mandates an algorithmic off switch, it creates a regulatory laboratory.

1. The user response: If users switch to chronological feeds, engagement metrics will drop. Platforms will then have to decide whether to monetize through other means or accept lower growth.
2. The competitive response: If domestic platforms must prioritize safety over engagement, they may find themselves at a disadvantage against global competitors who do not face the same constraints.
3. The political response: The US vote against the UN map change, which corrected the size of Africa, serves as a reminder that when institutional standards change, the actors who benefit from the status quo will resist. We should expect similar friction here:

"Advocates for this change say that diminishing Africa's size also subliminally diminishes its importance on the world stage. And beyond that, the map is just more accurate than it previously was."

-- Squiz Today Transcript

Just as the map change was about more than geography, the algorithmic debate is about more than what you see. It is about the power to define reality.

Key action items

• Monitor the legislative debate: Watch for amendments regarding the opt-in vs. opt-out structure. If the legislation shifts toward a default-off model, the impact on platform engagement will be immediate. (Next 30 days)
• Audit your own digital consumption: Use the current discourse as a prompt to manually switch your feeds to chronological order where possible. This creates a personal baseline for how much engagement you are currently being fed. (Immediate)
• Track platform compliance: Observe how Instagram, Facebook, and X implement the pop-up notification. If the prompt is buried in settings or designed to be ignored, the system is effectively neutralizing the regulation. (Next 3 to 6 months)
• Assess the cost of business vs. duty of care: If the laws pass, monitor whether platforms pay the fines or change their algorithms. If they pay the fines, it signals that the regulation is not yet strong enough to alter the systemic incentive structure. (12 to 18 months)
• Observe international ripple effects: If Australia successfully implements these laws, look for other nations to adopt similar digital duty of care frameworks, which will eventually force a global shift in how Big Tech manages algorithmic exposure. (18+ months)