Cost-Benefit Analysis: This is a method that compares the cost of an action to its expected benefits. It is used extensively in many areas such as environmental impact assessments, pharmaceutical research, and tech innovation projects.

Let's say you want to buy a new phone. You'll consider the cost (price of the phone, potential insurance, accessories) against the benefits (improved camera, more storage, better performance). If the benefits outweigh the costs, you'll likely buy the phone.

Complexities & Uncertainties: In large-scale cost-benefit analysis, it gets complex. Say, evaluating policies to prevent climate change. We need to calculate the value of ecosystems, the disruption costs, and mitigation costs. Plus, we have to factor in the unpredictable: the unknown unknowns. It's like trying to predict the outcome of a game of chess while you're still in the opening moves.

Post the nuclear catastrophe in 1986, Chernobyl was expected to be uninhabitable for centuries. But nature threw a curveball, and the ecosystem there is now thriving! There are more wolves inside the exclusion zone than outside. It's a sobering example of how difficult it can be to predict environmental impacts and the resilience of our natural environments. Think of it like a movie plot twist that no one saw coming.

Social Cost of Carbon: This refers to the economic damages caused by an additional ton of carbon dioxide emissions. It's a crucial measure in tackling climate change.

Remember how we used to pay for plastic bags at the store? That's a tiny example of the social cost of carbon: you pay a small cost to reduce the harm to the environment.

Problematic Aspects of Cost-Benefit Analyses: Such analyses are not infallible. They can be influenced by the biases of the estimators and can be misleading if accepted without critical thinking.

Consider online reviews while buying a product. They're a type of cost-benefit analysis, and we know they can sometimes be misleading, right? The same principle applies here, just on a larger scale.

Quantitative Justifications and the Dangers: While numbers can offer seemingly convincing justification for decisions, they can also be misused or misconstrued leading to false conclusions.

Ever seen a TV commercial that says 9 out of 10 people recommend a product? Well, remember to ask, "Who are these 10 people?" and "How was the testing conducted?" That's the kind of skepticism needed in assessing these justifications.