2. Examples of Risk Perception

Here is a very important data, then what is risk? Why people are not believing risk? there is a Britain Royal Society; they publish a White book on risk assessment in 1982 and in 1983, it was revised again.

This chunk introduces the concept of risk and raises two questions: what is risk, and why do people often doubt the existence of risk? The mention of the Britain Royal Society's publication indicates that the understanding of risk has been formalized and debated within academic circles. The Royal Society's involvement signifies the importance of this topic.

Imagine you are about to cross a busy street. You can see the cars speeding by, and you know that crossing at a red light can be dangerous. That knowledge represents the risk. However, sometimes, people may underestimate this risk and cross the street without looking, thinking, 'It won't happen to me.' This highlights the disconnect between knowing a risk exists and believing it truly applies to oneself.

Experts and scientists are called and but disagreement continued about risk.

This chunk signifies that even among experts, there is no consensus on what constitutes risk. It emphasizes that multiple perspectives exist regarding the evaluation of risks, reflecting the complexity of understanding risk in society. Risk can be viewed differently depending on individual experiences, cultural backgrounds, and scientific interpretations.

Consider a group of doctors discussing the risks of a new medication. One doctor might emphasize the potential for serious side effects, while another might focus on the benefits it provides to patients. This difference in perspective shows how even experts can disagree on the assessment of risk.

So, actual risk we as scientists saying that we there is actually an actual risk, what is that? So, we are saying that there are 2 kind of risk; one is objective risk that is scientific risk; another one is the perceived risk.

This chunk identifies two kinds of risk: objective risk and perceived risk. Objective risk is based on scientific data and facts, while perceived risk reflects what people believe about risks based on their experiences and emotions. This distinction is crucial for understanding how public opinion can differ from scientific consensus.

Think of a roller coaster. The objective risk—calculated by engineers—might show that it's safe, based on data from safety tests. Yet, someone who is afraid of heights may perceive riding the roller coaster as very risky. Their fear shapes their personal view of that risk, regardless of the facts.

So, determinant of risk; how we determine a risk? Generally, we determine any kind of risk by numerical measures, like expressed in chance of that much cost in dollar or in rupees, loss is expected to due to a flood...

This chunk discusses how risks are quantified using numerical measurements. By assigning a dollar value or probability to potential losses, we can assess the impact and likelihood of various risks more effectively. This quantitative approach allows for clearer communication of risks but may overlook subjective factors.

Consider a city planning to build a new bridge. Engineers will assess the risk of flooding by estimating potential economic losses in terms of millions of dollars. If flooding occurs, the cost of repairs and losses to transportation could total a significant amount, which is a straightforward way to express risk numerically.

So, probability and magnitude often adverse event. Now, risk estimation progress; if we want to progress more if you want to refine our estimation, one thing is very clear that we need data...

This chunk emphasizes the importance of data in refining risk estimations. The more data available about past events, the more accurate and detailed risk assessments can become. This highlights a fundamental element in risk analysis—using empirical evidence to make predictions about future risks.

Think of a weather forecasting service that uses historical weather data, like rainfall, temperature patterns, and storm occurrences, to predict future weather events. The more comprehensive their data collection, the better they can estimate the risk of severe weather occurring in a particular area.

So, but they are making it very simple, the scientists are saying that you need data but remember that risk perception that is subjective risk, what laypeople think...

This chunk points out the challenges in disaster risk management due to subjective risk perceptions held by the public. While scientists emphasize a data-driven approach, they also acknowledge that people's beliefs and fears can differ significantly from actual risks. Bridging this gap is crucial for effective risk communication and management.

Imagine a community preparing for a hurricane. Scientists might assess a category 5 hurricane as very dangerous, emphasizing the risk. However, if the residents feel invulnerable or believe they've faced worse storms without issue, they might ignore safety precautions. Understanding and addressing these feelings is essential in encouraging proper responses.

For example here, if you are smoking you are at risk, you believe or not you may be doing it because you want to be macho...

This chunk provides practical examples of risks that are both scientifically proven and subjectively perceived. Smoking and not wearing a seatbelt are highlighted as behaviors where individuals often dismiss objective risks due to personal beliefs or social pressures.

When one decides not to wear a seatbelt while driving, even though they know it could save their life, they might feel that it’s uncomfortable or unnecessary. This decision illustrates how personal perception of danger can lead to risky choices, contrasting with the objective risk of serious injury in an accident.

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