Confirmation bias occurs when people actively search for and favor information or evidence that confirms their preconceptions or hypotheses while ignoring or slighting adverse or mitigating evidence. It is a type of cognitive bias (pattern of deviation in judgment that occurs in particular situations - leading to perceptual distortion, inaccurate judgment, or illogical interpretation) and represents an error of inductive inference toward confirmation of the hypothesis under consideration. It can also be considered a type of selection bias in collecting evidence.
Data mining is defined as using sophisticated data search capabilities and statistical algorithms to discover patterns and correlations in data sets to discover new meaning in data. While appropriate use of data mining can help improve life it can also be abused and misused for intentional nefarious purposes. Yet a hidden danger is purported "experts" with narrow vision mining data with good intent not understanding unintended negative consequences.
One macro goal of data science is to define with precision important things to advance life, society and human evolution. More things we can't seem to define with precision yet:
Seasoned data scientists DEFINE WITH PRECISION things to apply certain conceptual frameworks to achieve specific goals. Without precise definitions data science results and interpretations are meaningless and present an illusion of reality and may cause damage. Here is a partial list of things we can't seem to define with precision yet:
The future of data science is bright and those who practice data science at a high level are blessed with fascinating work, wealth and high quality of life. The universe grants us exceptional privileges along with an obligation of NOBLESSE OBLIGE - the sacred duty to make life better for all people.
Practicing noblesse oblige means professional data scientists apply data science for the benefit of society - especially for those less fortunate. Factoring human rights and civil liberties is necessary.
Let us together use data science to create an awesome future for all.
Professional data scientists automate smart decision making processes using an assortment of tools including technology, artificial intelligence, deductive and inductive logic, experimentation and real-world experience. Yet human free will is an important consideration.
The Internet of Things (IoT) has the potential to improve life. The IoT is defined as equipping all physical and organic things in the world with small intelligent devices allowing near real-time collecting and sharing of data between machines and humans.
Seasoned data scientists apply the "precautionary principle" - defined as considering the potential for causing harm when experience and knowledge is lacking. Yet taken to extremes the precautionary principle can disrupt life and society and cause significant economic, health, social cohesion and human rights damage. For example, during COVID19 the policy of draconian lockdowns caused massive damage for little, if any, benefits.
One goal of the Data Science Team is to optimize decision-making at all levels of the organization: strategic, tactical and operational. Making consistently better decisions every day creates significant competitive advantages.
Elite performing leaders understand the need for smart data and advantages that result from evidence based - data-driven decisions. The collection and analysis of relevant high quality data is now an important part of both strategic and operational decision-making.
Seasoned data scientists develop and execute a solid information strategy. Many data science teams have a data analytics strategy without a prudent information strategy. Exactly what information is needed to achieve specific goals?