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Daniel Kahneman: Unraveling “Noise” in the World of Decision-Making


Welcome to an extraordinary journey into the mind of one of the most influential thinkers of our time. In this exclusive interview, we delve into the thoughts and experiences of renowned psychologist and economist, Professor Daniel Kahneman. As a Nobel laureate for his groundbreaking work in behavioral economics, Kahneman’s insights have revolutionized our understanding of human decision-making processes.

Deeply intrigued by the enigmatic workings of the human mind, Kahneman has spent decades unraveling the mysteries behind our cognitive biases and irrational behavior. His research has provided valuable insights into how we make choices, assess risks, and perceive reality. By shining a light on the intricate interplay between intuition and rationality, he has fundamentally transformed our understanding of human psychology.

Through the course of this interview, we aim to gain a deeper understanding of the man behind the groundbreaking theories. We explore the intellectual journey that led him to challenge traditional economic assumptions and develop the groundbreaking concept of prospect theory, which profoundly reshaped our understanding of risk aversion and decision-making under uncertainty.

As we embark on this unique opportunity to interview Daniel Kahneman, we invite you to join us on a thought-provoking journey into the mind of a Nobel laureate, whose pioneering research has forever changed our understanding of the human mind and its intricacies.

Who is Daniel Kahneman?

Daniel Kahneman is a renowned psychologist and Nobel laureate in economics, known for his groundbreaking research on human judgment, decision-making processes, and behavioral economics. Born on March 5, 1934, in Tel Aviv, Israel, Kahneman’s work has had a profound impact on various fields, including psychology, economics, and public policy.

Throughout his illustrious career, Kahneman has made significant contributions to our understanding of the cognitive biases and heuristics that shape human thinking and decision-making. His pioneering investigations into prospect theory challenged the conventional economic theory of rational decision-making, demonstrating that individuals often deviate from rationality due to inherent biases and psychological factors.

Kahneman’s collaboration with Olivier Sibony and Cass R. Sunstein writed the book named “Noise: A Flaw in Human Judgment”. In this book, the story follows a diverse ensemble of characters from different walks of life, each grappling with their own relationship to noise. His another influential book, “Thinking, Fast and Slow,” has become a seminal work, dissecting the dual systems of thought that drive our decision-making processes. Today, Daniel Kahneman continues to inspire and challenge scholars, policymakers, and individuals alike, as he continues to explore the intricacies of the human mind and its biases.

In recognition of their influential work, Kahneman and Tversky received the Nobel Prize in Economic Sciences in 2002, cementing their status as pioneers in the field of behavioral economics. This honor marked a significant milestone, as it emphasized the importance of understanding human behavior in economic decision-making, challenging traditional economic assumptions.

Aside from his academic achievements, Kahneman has also played a crucial role in applying behavioral science to public policy and organizational decision-making. His insights have influenced policymakers, business leaders, and professionals seeking to improve decision-making processes and optimize outcomes.

With his groundbreaking research and remarkable contributions to the field of psychology and economics, Daniel Kahneman continues to inspire scholars and practitioners alike. Through his work, he has fundamentally reshaped the way we understand human decision-making and provided invaluable insights into the complexities of the human mind.

Here you can know more about him by clicking Daniel Kahneman’s twitter.

20 Thought-Provoking Questions with Daniel Kahneman

1.Can you provide ten Noise quotes to our readers?

1.The illusion that one has understood the past feeds the further illusion that one can predict and control the future.

2. Our comforting conviction that the world makes sense rests on a secure foundation: our almost unlimited ability to ignore our ignorance.

3. We are prone to think that what we see is all there is.

4. When faced with a difficult question, we often answer an easier one instead, without realizing the substitution.

5. A coherent story gives us the illusion that we have a good understanding of the world, when we actually have no idea what is going on.

6. The confidence we have in our beliefs is not a measure of their quality, but rather of the coherence of the story we have constructed.

7. We can be blind to the obvious, and we are also blind to our blindness.

8. The more we learn about the limits of our knowledge, the more likely we are to rely on a seemingly relevant but actually irrelevant piece of information.

9. Our decisions are shaped by the noise in our minds, more than by the signal in the information we receive.

10. Noise is a major source of errors in judgments, and it cannot be eliminated entirely, but it can be reduced.

2. What motivated you to write this book? Why is addressing the issue of noise important to you?

Addressing the issue of noise is important to me because it represents a significant and often overlooked source of error in human judgment.

I previously emphasized the impact of random variability or “noise” on decision-making processes. Noise refers to the inconsistency or randomness in judgments made by different individuals faced with the same decision problem. While biases like systematic errors (referred to as “cognitive biases”) have received attention, noise has been less recognized as a factor affecting decision quality.

By addressing the issue of noise, I aim to shed light on its detrimental effects and advocate for reducing uncertainty in decision-making. I believe that understanding and mitigating noise can lead to better outcomes, especially in fields where subjective judgments play a crucial role, such as law, medicine, and human resources.

Furthermore, I recognize that noise can often be reduced by implementing measures such as clearer guidelines, calibrating judges, and using algorithms to make decisions more consistent. By emphasizing the importance of addressing noise, I hope to encourage organizations and individuals to take steps towards minimizing this source of error and improving the overall quality of decision-making processes.

3. How does “noise” differ from “bias”? Can you explain the concept and its implications?

“Noise” and “bias” are two distinct sources of error in decision-making and judgments.

Bias: Bias refers to systematic errors or consistent deviations from rationality or accuracy. It occurs when there is a tendency to favor certain judgments or decisions over others due to cognitive or situational factors. Biases can be influenced by heuristics, personal beliefs, emotions, or social pressures. For example, confirmation bias is the tendency to seek out information that confirms preexisting beliefs while ignoring contradictory evidence.

Noise: Noise refers to random variation or inconsistency in judgments or decisions that should be identical or highly similar. It represents the unwanted variability that occurs even when decision-makers have access to the same information and use the same decision rules. Noise can be caused by factors such as fluctuations in attention, mood, fatigue, or other irrelevant influences. Inconsistent decisions resulting from noise can lead to discrepancies, inefficiencies, and unfairness.

The implications of noise and bias are significant:

Bias can lead to systematic errors and distortions in decision-making processes, potentially resulting in suboptimal outcomes. Recognizing and mitigating biases is crucial to improve decision quality and accuracy.

Noise can undermine consistency and fairness in judgments and decision-making. It can cause different decisions to be made for the same case or lead to inconsistent evaluations within a group. Reducing noise is important to achieve more reliable and predictable outcomes.

Understanding both noise and bias is essential for improving decision-making systems and practices. Organizations can benefit by implementing strategies to reduce noise and mitigate biases, such as using structured decision protocols, providing feedback, training decision-makers, or employing algorithms to automate decisions.

4. In your book, you mention that noise can occur in various domains. Could you discuss some specific areas where noise frequently arises?

Legal judgments: Judges may exhibit inconsistencies when making decisions, even when faced with similar cases. This variability can be attributed to noise within the legal system.

Medical diagnoses: Doctors may arrive at different diagnoses for the same patient due to variations in interpretation or subjective judgment, especially when presented with complex or ambiguous cases.

Performance evaluations: Managers evaluating employee performance might differ substantially in their ratings, indicating the presence of noise. This can lead to unfairness and inconsistency in rewarding or promoting employees.

Loan approvals: Loan officers may grant or deny loans inconsistently, influenced by personal biases or other extraneous factors rather than purely objective criteria. This introduces noise into the lending process.

Hiring decisions: Interviewers’ judgments during the hiring process can be affected by noise. Multiple interviewers may have different perceptions of the same candidate’s qualifications and potential, leading to inconsistent outcomes.

5. What are some common misconceptions or misunderstandings people have about noise in decision-making?

Misconception: Consistency in decisions indicates accuracy.

Explanation: Many assume that if a group of people consistently make the same decisions, those decisions must be accurate. However, noise refers to random variability in judgments or decisions that is unrelated to the true underlying values. Even when people are consistent with each other, they may still be consistently wrong.

Misconception: Noise is identical to bias.

Explanation: While both noise and bias contribute to errors in decision-making, they operate differently. Bias refers to systematic deviations from the truth, while noise reflects random fluctuations around the true value. Reducing bias alone does not necessarily address the issue of noise.

Misconception: Noise is solely caused by human error.

Explanation: Although human judgment plays a significant role in introducing noise, it is not the only source. Noise can also emerge due to inconsistent procedures, ambiguous tasks, or variations in context. External factors like time pressure, distractions, or environmental factors can also contribute to noise.


6. Could you share some real-life examples to illustrate the effects of noise and how it can impact decision outcomes?

Judicial Sentencing: Studies have shown that noise can significantly influence judicial decision-making. For example, research has found that different judges may hand down different sentences for similar crimes, highlighting the role of noise in the justice system. This inconsistency demonstrates how random factors can introduce variations in decision outcomes, which should ideally be based on objective criteria.

Hiring Decisions: Noise can also affect the hiring process. When multiple interviewers assess candidates independently, each evaluator’s subjective biases and idiosyncrasies can lead to inconsistent evaluations. In one study, it was found that different interviewers’ opinions of the same candidate varied significantly, suggesting the potential impact of noise on hiring outcomes.

Medical Diagnoses: Noise can influence medical professionals’ diagnoses, potentially leading to diagnostic errors and varied treatment recommendations. Research has revealed that ordering a test multiple times for the same patient may yield different results due to noise, such as lab technicians’ interpretation or differences in equipment calibration. These variations in results can affect subsequent medical decisions.

Financial Decision-Making: Noise can have a significant impact on financial decision-making. Stock market prices often exhibit fluctuations caused by noise, which can lead investors to make suboptimal choices based on short-term market noise rather than long-term fundamentals. Additionally, financial analysts’ individual biases and their interpretations of company data can introduce noise that affects investment decisions.

7. How do individual decision-makers contribute to noise? Are certain personality traits or cognitive biases more prone to causing noise?

Individual decision-makers can contribute to noise through a variety of mechanisms. One important factor is inconsistency in judgment or decision-making. Even when faced with identical situations, individuals may produce different judgments due to random fluctuations or situational factors that should not influence the decision.

Certain personality traits and cognitive biases can indeed make individuals more prone to causing noise. For example, individuals who are highly impulsive or susceptible to emotional influences may exhibit greater variability in their decisions, leading to more noise. Additionally, cognitive biases like anchoring, availability heuristic, or overconfidence can introduce noise by distorting judgment and decision-making processes.

Personality traits such as high openness to experience or low conscientiousness might also increase susceptibility to noise. These traits can lead to a broader range of perspectives and less consistency in decision-making. However, it’s important to note that noise can arise from various sources and is not solely dependent on specific personality traits or cognitive biases.

To reduce noise effectively, it is necessary to identify and understand its sources. This involves careful measurement, analysis, and consideration of potential biases at every stage of the decision-making process. Implementing structured decision-making protocols, providing clear guidelines, and using algorithms or decision aids can help mitigate the contribution of individual decision-makers to noise.

8. Can you highlight any organizational factors that contribute to noise, and how can they be mitigated?

Firstly, decision-making processes within organizations often involve multiple individuals or teams working independently. This can lead to inconsistencies due to differences in judgment, interpretation of data, or personal biases. These inconsistencies contribute to noise, as decisions become less reliable and less accurate.

Another factor is the lack of clear and well-defined criteria for decision-making. When standards are vague or subjective, it allows room for noise to enter the process. Different individuals may interpret criteria differently, resulting in inconsistent outcomes.

To mitigate noise in organizational decision-making, here are a few strategies:

Standardization: Establishing clear guidelines, protocols, and decision frameworks can help reduce noise. Defining specific criteria and providing explicit instructions for decision-makers ensures more consistent outcomes.

Training and calibration: By providing training on decision-making principles and techniques, organizations can help individuals make better judgments. Calibrating decision-makers by providing feedback and comparing their judgments against objective benchmarks also helps reduce noise.

Decision support tools: Implementing decision support systems that incorporate algorithms or statistical models can help overcome human biases and inconsistencies. These tools provide a structured approach to decision-making, minimizing the impact of noise.

9. In your opinion, what are the main consequences of noise on society and individuals?

In the context of society and individuals, noise can have several significant consequences:

Inaccurate decisions: Noise can lead to inconsistent and erratic decision-making. When noise is present, judgments and choices can fluctuate even when the underlying circumstances remain constant. This inconsistency can result in suboptimal decisions and negative outcomes.

Reduced fairness: Noise can introduce bias and unfairness into various systems, such as hiring, criminal justice, and evaluations. It can cause discrepancies in judgment between individuals who should be making similar decisions, leading to unjust outcomes.

Impacted productivity and efficiency: Noise can hinder productivity by introducing unnecessary variations that distract from the task at hand. Whether in professional settings or personal lives, excessive noise can derail focus and hinder performance.

Decreased trust: Noise erodes trust in decision-making processes. If decisions are perceived as being inconsistent or arbitrary due to noise, people may lose faith in the fairness and reliability of those making the decisions.

Diminished well-being: Noise can generate stress and anxiety, affecting individuals’ mental and physical well-being. Constant exposure to noise can lead to health issues, sleep disturbances, decreased concentration, and overall dissatisfaction.

10. What are the key findings from research studies on noise that you discuss in your book?

Noise is pervasive: Research demonstrates that noise exists across various domains, including medical diagnoses, legal decisions, performance evaluations, and financial forecasting. It affects professionals in different fields and is not limited to specific individuals or organizations.

Noise is costly: The consequences of noise are significant, leading to errors, inconsistencies, inefficiencies, and unfairness. Noise can result in inconsistent judgments for similar cases or decisions, even when the same information is available.

Noise is distinct from bias: While bias refers to systematic errors in judgment, noise refers to random variability. Bias occurs when judgments consistently deviate from the truth in one direction, while noise produces inconsistent judgments that may vary unpredictably.

The magnitude of noise: Studies have found that noise can be substantial, often larger than the effects of bias. Different professionals assessing the same case can provide significantly different judgments, indicating a high level of noise.

11. How does the concept of noise relate to other concepts you’ve explored in your previous work, such as heuristics and biases?

The concept of noise is closely related to other concepts I have explored in my previous work, such as heuristics and biases. While heuristics and biases focus on systematic errors in judgment and decision-making, noise refers to the random variability that affects our judgments and decisions.

Heuristics are mental shortcuts that we use to simplify complex tasks, allowing us to make quick judgments and decisions. These heuristics can often lead to biases, which are systematic deviations from rationality. Biases arise due to the predictable ways in which our minds process information and make judgments.

On the other hand, noise captures the opposite phenomenon: the unpredictable, random variability in our judgments and decisions. Noise arises from both internal sources, such as mood fluctuations or momentary distractions, and external sources, such as ambiguous information or irrelevant situational factors. It can cause significant inconsistency and randomness in our decision-making processes, leading to errors and inefficiencies.

While biases and noise represent different aspects of human judgment and decision-making, they both contribute to suboptimal outcomes. Biases introduce systematic errors, while noise introduces random errors. Understanding and addressing both biases and noise are crucial for improving decision-making and achieving more accurate and consistent results.

12. Are there any situations or contexts where noise can be beneficial or advantageous?

Exploration and innovation: In fields that require creativity or discovery, such as art, research, or entrepreneurship, introducing noise can stimulate divergent thinking and help explore unconventional ideas. Noise may lead to novel solutions that otherwise might not have been considered.

Decision diversity: In group decision-making processes, allowing for some level of noise can promote diversity of opinions. This diversity helps avoid groupthink, where individuals conform to a dominant viewpoint, which can lead to suboptimal decisions. By incorporating a degree of noise, a wider range of perspectives can be considered, enhancing the chances of finding better solutions.

Risk management: In risk assessments and predictions, including noise factors can account for the inherent unpredictability of certain events. Noise acknowledges that outcomes cannot always be precisely determined and provides a more comprehensive understanding of potential risks and uncertainties.

Adaptive systems: Some complex systems, such as ecosystems or economies, benefit from noise as it allows for adaptation and resilience. Introducing random variations can help these systems respond to changing conditions, maintain stability, and avoid being overly influenced by specific events or circumstances.

13. Is there a threshold beyond which noise becomes particularly detrimental? How can we determine whether noise levels are acceptable or excessive?

To determine whether there is a threshold beyond which noise becomes particularly detrimental, we need to distinguish between noise and meaningful variation. Some variability in judgments can be attributed to legitimate factors like differing perspectives or information gaps. However, excessive noise can lead to inconsistent decisions, reduced accuracy, and inefficiencies.

Identifying the acceptable or excessive levels of noise requires a combination of empirical research and subjective judgment. Here are some steps we can consider:

Quantify noise: Conduct studies where multiple assessors independently evaluate the same set of cases. By comparing their judgments, we can measure the extent of variability among them. Statistical methods, such as inter-rater reliability coefficients, can help quantify noise levels.

Benchmark against theoretical expectations: Establish baseline expectations for consistency based on theoretical models or existing norms within a specific domain. This enables us to compare observed levels of noise against what is theoretically expected.

Assess impact: Evaluate the consequences of noise on decision quality, fairness, efficiency, and overall performance. Determine how much noise affects outcomes, such as accuracy, agreement, and fairness between decision-makers. Excessive noise can potentially lead to errors, biases, and suboptimal decision-making.

14. What strategies or interventions can individuals or organizations implement to reduce or manage noise effectively?

Standardization: Implement clear guidelines, protocols, and standard operating procedures to ensure consistency in decision-making processes. This reduces the variability caused by individual biases and preferences.

Checklists and algorithms: Develop checklists or decision-support tools that outline critical factors to consider when making decisions. These tools can help individuals and organizations avoid overlooking important information and minimize noise caused by random factors.

Training and feedback: Provide training programs that focus on improving decision-making skills, including recognizing and minimizing noise. Encourage feedback mechanisms to evaluate decision outcomes and learn from mistakes.

Diversity and collaboration: Promote diverse perspectives by including individuals with different backgrounds, experiences, and expertise in decision-making processes. Collaboration can help identify and mitigate sources of noise by bringing various viewpoints to the table.

Calibration and debiasing: Offer calibration training to improve accuracy and reduce overconfidence. Debiasing techniques, such as considering alternative hypotheses and seeking disconfirming evidence, can help counteract cognitive biases that amplify noise.


15. How does expertise or experience influence the occurrence of noise, and can it be leveraged to mitigate its impact?

Expertise and experience can play a significant role in mitigating the impact of noise. Noise refers to unwanted variability in decision-making outcomes that are unrelated to the variables being considered. It can influence judgments and predictions, leading to inconsistent results.

Expertise: Increased expertise generally leads to more accurate and reliable judgments by reducing noise. Experts have developed refined mental models, acquired specialized knowledge, and honed their skills through deliberate practice. This allows them to recognize patterns efficiently, filter out irrelevant information, and make more consistent decisions.

Experience: With experience, individuals become familiar with common sources of noise and learn to identify and address them effectively. They develop heuristics or rules of thumb that help streamline decision-making processes and reduce noise. Experienced professionals often possess a better understanding of contextual factors, enabling them to make more nuanced judgments.

To leverage expertise and experience in mitigating noise’s impact, several strategies can be employed:

Training and calibration: Providing training programs that aim to enhance expertise and proficiency can reduce noise. Calibration exercises help individuals understand their own biases and variability in judgments, encouraging greater consistency.

Standardization: Developing standardized decision-making protocols and guidelines can minimize noise caused by subjective interpretations. By implementing structured approaches, organizations can reduce variability across different decision-makers.

Collaboration and feedback: Creating environments that encourage collaboration and feedback among experts can help identify and correct individual biases. Group decision-making processes allow for diverse perspectives, which can counteract personal biases and reduce noise.

16. Can technology play a role in reducing noise? Are there any emerging tools or approaches that show promise in this regard?

Yes, technology can indeed play a role in reducing noise. Noise refers to the variability or inconsistency of judgments or decisions that arise from factors like personal biases, random influences, and subjective interpretations. By leveraging technological advancements, we can address these sources of noise and improve decision-making processes.

Emerging tools and approaches show promise in reducing noise by providing more standardized and consistent methods for decision-making. One example is the use of algorithms and machine learning models that can help automate certain decisions, minimizing human biases and inconsistencies.

Additionally, online platforms and collaborative tools can enable more structured and systematic decision-making processes, ensuring that relevant information is shared and considered by all stakeholders. These technologies can promote transparency, reduce individual biases, and enhance collective decision-making.

Furthermore, advancements in data analytics allow us to identify patterns, trends, and insights that were previously overlooked due to human limitations. By leveraging big data and advanced analytics techniques, we can extract valuable information from vast amounts of data, helping to reduce noise and make more informed decisions.

17. Are there any ethical considerations we should keep in mind when addressing noise in decision-making processes?

When addressing noise in decision-making processes, there are certainly ethical considerations that should be kept in mind. Here are a few key points to consider:

Fairness and Justice: Noise in decision-making can lead to inconsistent outcomes and unequal treatment of individuals in similar situations. It is important to address this issue to ensure fairness and justice. Ethical considerations call for treating people equally and avoiding arbitrary discrepancies caused by noise.

Bias and Discrimination: Noise can amplify bias and discrimination in decision-making, leading to unfair outcomes. Addressing noise involves examining the sources of bias and implementing measures to minimize their impact. An ethical approach requires actively working towards unbiased decision-making and reducing discriminatory practices.

Accountability and Transparency: Noise can make it difficult to hold decision-makers accountable for their actions. Ethical considerations demand transparency in decision-making processes, enabling scrutiny and evaluation of the factors contributing to noise. By ensuring accountability, we can reduce the potential for unethical behavior or negligent decision-making.

Trust and Reputation: Noise can erode trust in decision-making systems and organizations. Ethical considerations involve prioritizing trust and maintaining a good reputation. Taking steps to reduce noise helps rebuild trust and confidence in the decision-making process, both internally within organizations and externally with stakeholders.

18. As a society, what steps can we take to raise awareness about the issue of noise and its consequences?

Here are some steps that society can take to achieve this:

Education and Research: Firstly, we should invest in research to better understand the effects of noise on individuals’ well-being, health, and cognitive functioning. This will provide us with concrete evidence to support our awareness campaigns. Additionally, educational programs should be developed to inform people about the various sources of noise pollution, its impact on mental and physical health, and strategies to mitigate its harmful effects.

Public Awareness Campaigns: Launching public awareness campaigns is crucial to grab people’s attention and stimulate discussion around the issue of noise pollution. These campaigns should utilize diverse communication channels such as social media, television, radio, and print media to reach a wide audience. They can highlight the negative consequences of noise, emphasizing the detrimental effects on sleep, concentration, productivity, stress levels, and overall quality of life.

Engaging Stakeholders: It is essential to involve relevant stakeholders, including government bodies, urban planners, architects, engineers, and health professionals, in addressing the issue of noise pollution. By collaborating with these groups, we can create guidelines and policies aimed at reducing noise levels in public spaces, residential areas, and workplaces. Promoting innovations in noise reduction technology and architectural design can also be instrumental in minimizing noise pollution.

19. How do you envision the future of research on noise? Are there any specific areas that require further investigation?

To investigate noise further, I would propose several specific areas that require attention:

Measurement and quantification of noise: Developing reliable and validated methods to measure noise levels in various domains such as healthcare, finance, and justice systems is crucial. This involves identifying sources of noise, understanding its impact, and establishing metrics to quantify its effects.

Impact on decision quality and outcomes: Assessing how noise affects decision quality, accuracy, fairness, and consistency across different contexts is necessary. Investigating the consequences of noise on judgment and decision-making outcomes can help identify areas where improvements are needed.

Causes and mechanisms of noise: Understanding the underlying causes and mechanisms that lead to noise is essential for effective interventions and decision-making improvements. Exploring cognitive, organizational, and situational factors that contribute to noise will provide insights into how it can be minimized or managed.

Mitigation strategies: Developing practical strategies to reduce or eliminate noise is crucial. Investigating the effectiveness of interventions such as training programs, decision aids, automation, and feedback systems can help identify approaches to mitigate the impact of noise.

20. Finally, can you recommend more books which can influence readers like Noise?

Wiser” by Cass R. Sunstein, it provides a much-needed guide for navigating the complexities of decision-making. Whether you are a student, professional, or simply someone seeking to enhance their judgment, this book is a valuable resource that will leave you pondering the potential of collective intelligence and its impact on our world.

Influence” by Robert B. Cialdini, this influential work explores the principles and mechanisms behind human persuasion and reveals how individuals can be influenced, often subconsciously, by various techniques used by compliance professionals.

Crucial Confrontations” by Kerry Patterson, it serves as an essential guide to effectively resolving difficult conflicts and addressing crucial conversations that arise in both personal and professional settings. It is a transformative resource that enables readers to embrace confrontation as an opportunity for growth, build healthier connections, and achieve better results in all areas of life.

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