Report Influence of artificial intelligence

Since 1990 is the technological development was significantly enhanced a significant improvement was evident in performing different tasks. The concept of artificial intelligence in the area of science is closer to fiction. However, the main idea is no longer a fiction, but it is a reality that has induced impact on daily life (Poola, 2017). Machine learning is a process in which neural networks are used for external processes as well as actual processes for the real neurons. Artificial intelligence has a wide range of application in real life and according to the future perspective, it will overwhelm the science and fiction (Jordan & Mitchell, 2015). The combination of artificial intelligence with machine learning enables complex data processing and provides accurate information (Shabbir & Anwer, 2015). With the development and innovation of artificial intelligence, the golden age of artificial intelligence dominated the focus of technology in an improved way. Notably, the artificial intelligence integration improved activities of people along with connectedness. The term artificial intelligence also refers to the ability and capability to resolve the issues. The integration of artificial intelligence is related to different functions such as memory, planning, language, attention, and person perception (Brookings. edu, 2015).  In the previous 10 years, stages of evolution of intelligence are becoming an interesting subject of research. Machine learning can be described as a discipline that is focused on two main interrelated questions including a procedure to construct computer system that automatically improve the experience and fundamental statistical computer additional information on theoretical laws for the computer system in the organization (Intellipaat. com, 2018). Machine learning addresses the practical implementation of computer software and fundamental scientific applications. In the past two decades, the progress of machine learning is dramatically improved with the widespread uses of artificial intelligence. Many developers working with artificial intelligence systems are now considering applications of machine learning (Interesting engineering. com, 2017).  The effect and advancement of machine learning are broadly accepted in the computer science field and industries that are concerned with the consumer services, data-intensive issues, controlling of logistic change, and diagnosing the fault in the complex systems (Blockdelta. io, 2018). In different respects, machine learning methods are developed to analyze experimental data embedded with functions to improve the accuracy of experience.  In the case of sustainable organizational performance, the machine algorithm is developed to deal with a variety of problems and data (Shabbir & Anwer, 2015). The conceptual machine learning algorithms are provided with the optimize performance metric and training experiences of the program. The machine learning algorithms can be used to deal with the decision trees, general language programs, and mathematical functions in the organization (Forbes. com, 2018).

The evolution converters methods are developed to evaluate the generator successive conditions and deal with different approaches. The purpose of the present work is to define future influences of artificial intelligence in our daily life.  With the passage of time, technology and artificial intelligence are growing by leaps and bounds (Shabbir & Anwer, 2015). Despite the facts of proper use of technology for unemployment and overdependence, technology holds a bright future for the users. It can be concluded that technology is shaping our future in a better way. In the sequence of this condition, present work is based on an evaluation of the data for individual performance and project management processes in different organizations (Jordan & Mitchell, 2015). Under these considerations, the aim of present work is to identify the frameworks regarding the future perspective of machine learning and artificial intelligence and how it transforms the lives of users (Shabbir & Anwer, 2015; Jordan & Mitchell, 2015).

Aims and objectives of Influence of artificial intelligence

Artificial intelligence has substantially improved the lives of users in many ways. There is a number of applications associated with the implementation of artificial intelligence in organizations and real life (Jordan & Mitchell, 2015). The implementation of artificial intelligence leads to time-saving conditions and increases the output of the business from day by day human activities the development in artificial intelligence as well as machine learning procedures directed human effort to be reduced in many ways. The other applications are automatic transport system, computerized methods, and involvement of human beings in dangerous jobs (Shabbir & Anwer, 2015). It can be considered that the dramatic influence of artificial intelligence on human life open the doors of wonders related to the automatic process and activities. Different types of methods and manuals are used to complete the process. Looking forward to the automatic system of artificial intelligence in different procedures to be completed by reducing actual activities, enabling the process proceeds to move forward, and development of industries,  the role of artificial intelligence and machine learning is universally improved (Poola, 2017). The concern of present work is to identify the role of artificial intelligence and machine learning in human beings. Deep learning is considered for the development of technology and scratch surface frontiers applications in business.  The sophisticated machines are developed, and these machines can do work with the minimum human interventions. The major goal of the present research is to provide a guideline related to machine learning, dimensions and parameters of data points, complexity in the process, and classical computational resources to resolve the problems under defined frameworks (Shabbir & Anwer, 2015). The present deals with probability approximated correction and polynomial-time computation constraints to develop a relationship between learning algorithm, training data size, error rates, the advancement of research with lower bound conditions (Shabbir & Anwer, 2015).

Timeframes of Influence of artificial intelligence

The artificial intelligence is quickly becoming a reality. The statistical analysis of business and industry is the shows change of artificial intelligence and higher uses in the industries.  Implementation of state of art technologies under artificial intelligence alters the way of thinking and interaction with everyday procedures for instance manufacturing process, education, healthcare, investment in startups, big data, full market overview, voice search, virtual digital assistants, and recognition of statistical analysis about current state and future scope (Jordan & Mitchell, 2015; Shabbir & Anwer, 2015). The statistical analysis about the role of artificial intelligence in present as well as in future perspective are mentioned below,

1.      By 2025, the expectation with the global artificial intelligence market is about 16 billion dollars and previously in 2016, it was 1.4 billion dollars (Bigdata-madesimple. com, 2016).

2.      By 2030, the expected growth in global GDP is 15.7 trillion dollars.

3.      Increase in productivity is expected to be 40% (Forbes. com, 2018).

4.      In the past two decades, artificial intelligent status grew about 14 times more.

5.      By comparing with 2000 statistics, investment in artificial intelligence startups increased 6 times more.

6.      About 77% of devices are featured with state of the art technology (Intellipaat. com, 2018).

7.      Google statistical analysis has strong believed about the next year 2020, that robots will work the same as complex human behaviors such as flirting and joking (Shabbir & Anwer, 2015).

The statistics show the dependence of new system on artificial intelligence and how technology is evolving to improve the functionality and working conditions of organizations (Shabbir & Anwer, 2015).

Data collection of Influence of artificial intelligence

Currently artificial intelligence as the capability to intimate with human Intelligence and to perform a different task through proper procedures. The abilities of artificial intelligence are to perform different types of solving problems of taking the decisions and thinking about the learning procedures. The artificial intelligent machines and systems are in a position to deal with the tasks and exercise errors.  Currently artificial intelligence applications in robotic cars, controlling traffic, minimizing speeds, taking tension, and controlling the traffic (Shabbir & Anwer, 2015).

The research considered the use of artificial intelligence, technological development, and machine learning in different research areas. In order to identify the future perspective of artificial intelligence and machine learning, numerous consultations were carried out from secondary data such as journal articles, website and academic researches (Shabbir & Anwer, 2015). Connected with the conditions, the research embraces a new form of analysis based upon the previous research.  There are two methods use in the present to collect the data and information about the implementation of artificial intelligence and machine learning processes (Jordan & Mitchell, 2015). The first method is previously defined as secondary sources of information while on the other hand, the second method is to collect the data and information from the survey (Totalphase. com, 2017).

Data analysis of Influence of artificial intelligence

The artificial intelligence is creeping into the lives of human beings speedily through scanning machines and GPS  navigations. The implementation of artificial intelligence in the business have a higher contribution in potentializing of different areas of business, for instance, technical processes, customer service, administration, finance, sales, service, marketing, along with various factors (Shabbir & Anwer, 2015). No doubt with the past few years, the digital efforts were not isolated by technical processes in the companies. The digital efforts will be no longer isolated projects of the companies but also involves technology is at different levels at artificial intelligence to improve their competitiveness (Bigdata-madesimple. com, 2016). Artificial intelligence integrates the system activities to the business. The major role of artificial intelligence is on the replacement of human beings from the organization and workplaces. It enables the workers to develop creativity and potential at their maximum peak (Shabbir & Anwer, 2015). Introducing to new technologies in Companies, electronic action traceability and security considerations are required to take in confidence of Management. The present work deals with the improvement of artificial intelligence an efficiency of people while performing the works through machines and controlling the process (Shabbir & Anwer, 2015). This condition leads to a question about the level of performances in human beings, economic levels, and other conditions of work. The present work is about the future perspective of artificial intelligence Technologies and to compare it with human intelligence.  In the present work, we considered all the applied fields and develop the potential analysis of artificial intelligence technique, potential management, benefits, and improvement in the system (Jordan & Mitchell, 2015).

Future of Influence of artificial intelligence

Intelligence and machine learning becoming emerging Technologies that advance the systems.  Considerable attention is drawn towards the impact of public policy and Employment through artificial business in the workplace (Bigdata-madesimple. com, 2016). Some researchers worked on the impact of artificial intelligence on the development of robotics and if the Robotics becomes more advanced is it possible to take the jobs and what will be the impact of emerging technology on the public policy and Employment rates (Shabbir & Anwer, 2015). The present consideration includes improvement in emerging Technologies related to services cost of available good quality and speed. This technology replaces a large number of workers and minimizes the workforce. The impact of automation system through modern technologies is evidence through economic conditions (Shabbir & Anwer, 2015). World wild number of industrial developments is considered in service sectors fraction processes and computer algorithms. The business operation improves due to the higher trend of Technology in the workplace (Forbes. com, 2018). Some of the researchers and experts do not agree with the impact of automation technology on the workflows while on the other hand, some suggest segregation of unemployment through their services (Interesting engineering. com, 2017). The automation Technologies have a higher focus on the benefits of employment flexible Technology, the use of artificial intelligence in the industry expands and Income Tax credits. Perhaps, during the whole research work, proactive questions were raised in the paper about the future perspective of uses and activities (Shabbir & Anwer, 2015).

The increase in the improvement of artificial intelligence management systems is increasing. The idea of creating artificial intelligence levels the system to be working in a simple way and deliberate with the different advantages and different advantages. Many researchers identified different ideas of artificial intelligence that can be improved by considering different solutions for conditions (Jordan & Mitchell, 2015). The use of artificial intelligence increases profitability and generates higher economic growth rates. Addition two different innovative work the aim of artificial intelligence is too robotic technology in the industries. Artificial intelligence has revolutionized companies and system of production increases in the work (Shabbir & Anwer, 2015). Higher opportunities for work are developed that makes a procedure and work easier as compared to the previous Technology (Jordan & Mitchell, 2015). The role of human beings in the development of artificial intelligence is highly exclusive. The artificial intelligence machine system is ethical and moral values of the system increases with positive outcomes and higher engagement of customers and people with the production process (Poola, 2017). The advantages of artificial intelligence colonization of people living in different areas and have potential efforts to fight with free space with critical terms. Artificial intelligence has advantages in self-replicating procedures and investigation of different Technologies such as teleportation and cellular level travel (Intellipaat. com, 2018). The impact of artificial intelligence is higher in economic condition and execute stock trades for different Technologies in case of service sector computer algorithms are executing the sufficiently higher role. The technologies are becoming capable to do applications (Interestingengineering. com, 2017). Different experts are agreeing on the size of the impact of digital Technologies places four unemployment and Staging process. Flexible security is an idea to deal with education Healthcare and Housing assistance. The expansion of incomes and credits is proactively based on education and worth of the business (Intellipaat. com, 2018).

Application of Artificial intelligence

Self-driving cars of Influence of artificial intelligence

Artificial intelligence has boosted the transport system advancement in the technology is observed by considering self-driving Cars. Advancement in technology has utilized different safety processes development processes and car making procedures (Brookings. edu, 2015). The self-driving car moves around the ways. The technology is used to navigate crossroads and to reduce accidental issues. The technology behind self-driving Cars improves the lives of others and increases safety conditions for the people sitting in the car. A number of accidents are occurring due to substantially reduced concern and skills of driving (Blockdelta. io, 2018). The technology used in self-driving Cars is multiple times greater than previous searches. The factors that contribute to accidents include alcohol, drugs, lack of experience, aggressive driving, over speeding, ignorance of road signs, study reactions, and overcompensation over different conditions (Jordan & Mitchell, 2015). Statistical analysis shows that total accidents occurring during the alcoholic conditions and drug abuse are 40%. Consequently, more than 1100 drivers lost their lives along with the passengers, therefore, the implementation of self-driving Cars is especially required. From 2012, the US Department of Transportation is working on different levels of automated cars such as trains and buses (Shabbir & Anwer, 2015; Jordan & Mitchell, 2015).

Involvement in Dangerous Jobs of Influence of artificial intelligence

Artificial intelligence had developed reports that are human beings in critical conditions and hazardous situations.  These robots are taking positions of human being and doing dangerous jobs such as defusing bombs.  The development of robots to deal with diffusion of bombs is highly required to increase the life rates (Shabbir & Anwer, 2015). In these very boards are serving thousands of lives by doing dangerous jobs. Eventually, The Other applications include processing with toxic substances, working under intense heat, significant benefits of knowledge for environmental conditions, and safety measures for human beings to have protection from harm (Jordan & Mitchell, 2015).

The research conducted by BBC defined hazardous jobs conducted by robots. The technological drones are being developed to deal with the physical process of defusing the bombs and having control over the human being lives (Shabbir & Anwer, 2015). AI integration is used to improve the machine function. The research conducted by Robot Worx explained the role and process of robotic welding to deal with safety features and to prevent human beings from working with dangerous fumes (Jordan & Mitchell, 2015).

Computerize methods of Influence of artificial intelligence

The role of artificial intelligence is improved in computerized methods to perceive daily activities. The use of the navigation system and GPS system by the drivers is an example of artificial intelligence role in human life. The minimum occurrence of error is considered and observed in the prediction of the computer-based system (Intellipaat. com, 2018). Furthermore, artificial intelligence has used financial and banking management, organization of statistical data,  reducing the number of errors and issues and utilization of state of the art technology to reduce the number of errors and to improve the strategist of achievement. Besides other factors, artificial intelligence has a higher wall in medical research and diagnosis of complex disorders. Artificial intelligence has access to human health risks and medical research by using artificial intelligence lead to having an influence on the study of saving a life (Jordan & Mitchell, 2015; Poola, 2017).

Reduced Human Efforts by Influence of artificial intelligence

Implementation of artificial intelligence have an essential role in human life and to perform human activities. The consistent rate of production increases with effective strategies and management in the workplace. Implementation of artificial intelligence in the work process,  promises the error-free work, speeding up of the process, accuracy in the results, and production improvement ability (Shabbir & Anwer, 2015). The companies and management systems keep a record of work, extract the data, and the decision-making process is based upon the data collected in the company. Mainly, the role of artificial intelligence is associated with the production and processing of industries for having business development and good times. Artificial intelligence saves the time of human beings from solving complicated issues significantly improve the lives of the users of ai technologies (Jordan & Mitchell, 2015).

Cyborg technology of Influence of artificial intelligence

The human brain and body have limited functionalities and works for a complex situation.  Researcher Shimon Whiteson initiative to deal with the future of human beings by considering the state of the art technology (Totalphase. com, 2017). The use of computers in workplaces can increase natural ability to do work and this possible in enhancement is known as cyborg technology. There are different conditions according to convenience practical purposes. Under certain conditions, the brain works as a robotic limb and control significant conditions (Bigdata-madesimple. com, 2016).

Recommendation from evidence on Influence of artificial intelligence

Before the release of an artificial intelligence system, organizations should rigorously test for ensuring that they will not amplify errors and biases due to any problems with algorithms, training data, and other parts involved in the system design. Considering the fact that this is consistently changing field, assumptions and methods of testing together with results should be documented openly with transparent versioning for accommodating new findings and updates. Organizations developing and profiting from these systems must be accountable for leading the tests including pre-release trials. This field is far from involving standardized methods and that is the reason why testing methods should be open for discussion and scrutiny. This openness will be quite significant if the field of artificial intelligence is to develop robust methods of testing over time.

After the release of an artificial intelligence system, the organization should continuously monitor its usage across different communities and contexts. The outcomes and methods of monitoring must be defined through rigorous and open processes, and have to be accountable to the public. In high stakes contexts of decision-making, the experiences and views of marginalized communities must be prioritized. Making sure that algorithmic and AI systems are safe is very complex and has to be an ongoing procedure through the life cycle of the system at hand. It is completely different from a compliance checkbox that can easily be. Monitoring across dynamic contexts and use-cases are necessary for ensuring that AI systems do not introduce bias and errors as cultural domains and assumptions change and shift. It is also significant to keep it in check that not many models of AI have a general purpose where they might utilize add-ons like facial recognition for plug-and-play. It means that organizations providing general-purpose models of AI can also consider the choice of licensing for an approved use where risks and downsides have been considered.

More policy and research making is required on the utilization of artificial intelligence systems in the monitoring and management of the workplace including HR and hiring. Specific attention must be given to the potential effect of an AI system on labor practices and rights and must concentrate on the potential for unintended reinforcement and behavioral manipulation of bias in promotion and hiring. The discussion around labor and artificial intelligence normally focus on the displacement of labor, which is quite a serious issue. However, it is also very important to keep the track of just how algorithmic and AI systems are utilized within the workplaces at present for everything from rating performance to surveillance and behavioral nudging. Given the potential of artificial intelligence system in entrenching existing biases and reducing diversity, more work is definitely required for understanding how artificial intelligence is incorporated into practices, structures, scheduling, hiring, and management of workplaces.

It is also important to the development of various standards for tracking development, performance, and the utilization of datasets throughout the life cycle. This is crucial for better monitoring and understanding issues of representational skews and bias.  In addition to the development of better records for just how a dataset of training was maintained and created, measurement researchers and social scientists within the bias study field of AI should continue to test the existing datasets of training and work for understanding biases and blind sport that might already bet at the work. Artificial intelligence depends on data at a large-scale for making predictions and detecting patterns. Human history is reflected by this data and also reflects prejudices and biases from the dataset of training. Techniques of machine learning excel at picking such statistical designs, normally omitting the diverse outlier for generalizing common cases. Therefore, it is significant that research about bias should not consider data at the face value and it must begin by understanding where data utilized for training systems of AI came from and validating the assumptions and methods that shape a certain dataset over a specific time period. With an understanding of this, bias and errors reflected in data can be understood in a better way while also developing ways of mitigating them during the collection and creation of data.

AI bias mitigation and research should be expanded beyond a simple and narrow technical approach. Issues related to bias are structural and long-term, and contending with them seems to necessitate in-depth interdisciplinary research. Furthermore, the technical approach looking for a one-time solution for a fairness risk, oversimplify the complexity of a social system. In different domains such as criminal justice, healthcare, or education, bias's legacies and movements towards strong equality have their own practices and histories. These legacies cannot be resolved without depending on the domain expertise. Addressing fairness will need interdisciplinary methods and collaboration across different areas and disciplines.

The recent increment in the work in algorithmic and AI bias is actually an excellent sign. However, taking a purely technical approach is still not safe. After all, there is a risk that networks and systems are only optimized without any understanding of what to optimize for. It means that computer scientists can learn more about the underlying inequalities in terms of the structure that shape the data and contextual incorporation of artificial intelligence systems by collaborating with the experts of the domain in fields like communication, anthropology, sociology, medicine, and law. Powerful standards for understanding and auditing the use of artificial intelligence is complex systems is needed urgently. The development of such standards will need the perspective of diverse coalitions and disciplines. The procedure by which such types of standards are developed must be accountable publicly and subject to revision and review in a periodic manner.

At present, there are no established procedures for the assessment and measurement of the effects of artificial intelligence systems as they are utilized in certain social contexts. This is quite a significant issue, considering the determinations that AI systems are impacting across various domains. The development of such methods and standards should be the top priority for the field of AI. Conferences, universities, and companies along with other stakeholders in the field of artificial intelligence should release data on the involvement of minorities and women in the development and research of AI. Now, many seem to recognize that the present absence of diversity in artificial intelligence is an important issue which is required for measuring the progress. And beyond this, a deeper assessment of the cultures at workplaces is needed in the technology industry that needs going beyond the simple recruitment of minorities and women towards creating more inclusive workplaces.

The perspectives and assumptions of those who develop systems of artificial intelligence will shape them. Often, developers of artificial intelligence are male with similar backgrounds in terms of training and education. However, beyond the general diversity statistics of the technology industry, there are some efforts for better understanding of the problem of diversity in the field of artificial intelligence. If artificial intelligence is to be widely relevant, fair, and safe, efforts must be focused on tracking inclusion and diversity while ensuring that the culture in which artificial intelligence is being designed is welcoming to all types of experts. The industry of artificial intelligence should be recruit professionals from areas beyond engineering and computer science while making sure that they have the power of making decisions. With the movement of AI towards diverse institutional and social domains, affecting the emerging high-stake decisions, time and effort must be concentrated on the integration of legal scientists, social scientists, and others with the domain expertise capable of guiding the integration and creation of artificial intelligence into established practices and long-standing networks.

Just as a lawyer cannot optimize a DNN or deep neural network, a technical AI engineer or researcher cannot also be expected to be professionals in the criminal justice or any other type of social domain where the technical system is being incorporated. Domain experts must be there for helping the prime process of decision making while ensuring that systems of AI don't misunderstand the contexts, complex histories, and processes in sectors like education, health, and law. Ethical codes with the objective of steering the field of artificial intelligence must be supported by strong accountability mechanisms and oversight. Furthermore, more work is required on how to connect high-level guidelines and principles of ethics for best practices to the development processes, release cycles of product, and promotion on a daily basis.

Various groups of computing industry are developing the codes of ethics for ensuring the development fair and safe artificial intelligence but these codes are generally voluntary and high –level, asking the developers of AI to prioritize the general or common good. However, such codes will have to be interlinked to clear and precise systems of accountability while remaining aware of the power asymmetries and incentive structure at work in the industry of AI.

 Sustainable organizational performance of Influence of artificial intelligence

One of the most significant and powerful examples of modern environmentalism's limits is to push for green energy. For combating climate change and other types of pollution, it is significant to shift to geothermal, nuclear, wind, and solar sources of energy. However, while the technology exists to obtain a large area of energy from these sources, utilities and businesses have trouble integrating them into daily operations. Each method of generation is suited to companies in different areas and with distinct use needs of energy. Figuring out just which solution will offer the required outcomes takes a lot of time and efforts, and has a great potential for error. Applications of AI can determine how to implement green energy far more effectively and quickly than human planners are capable of. Companies can feed that data regarding energy to an application of AI which can compare these patterns to all the available sources of sustainable energy, and identifying the one which meets the requirements of organization properly while generating extra-costs as minimum as possible. Artificial intelligence can also determine the potential roadblocks in the process of adoptions so companies are prepare to minimize those issues.

In addition to the climate and pollution change, humanity is actually having a profound impact on wildlife ecosystems and populations. As the usage of land is increasing, it is becoming less for the life of plants and animals that play a significant role in the regional and local environments. Although private initiatives and local governments try to limit this type of threats, understanding what areas and resources need to be saved for wildlife population is the key to effectively protect ecosystems. Systems of artificial intelligence have the capability of resolving this issue. By analyzing the extensive data on migration and feeding patterns of wildlife, AI applications can offer intelligence on what areas should be saved for keeping the wildlife ecosystem safe. This way, sustainability can be maintained with the use of artificial intelligence (Villa, Ceroni, Bagstad, Johnson, & Krivov, 2009).

Conclusion on Influence of artificial intelligence

Overall, it can be said that artificial intelligence plays a very important role in not only supporting technologies but also enhancing the capabilities of organizations operating at different levels. Artificial intelligence as technology is quite close to fiction as it enables the development of applications that are beyond the traditional processes of development. Artificial intelligence has substantially improved the lives of users in many ways. There is a number of applications associated with the implementation of artificial intelligence in organizations and real life. Currently artificial intelligence as the capability to intimate with human Intelligence and to perform a different task through proper procedures. The abilities of artificial intelligence are to perform different types of solving problems of taking the decisions and thinking about the learning procedures. AI not only plays an integral role in the development of applications but it also assists in the maintenance of sustainability of the environment. Organizations can use applications of artificial intelligence to keep sustainability in check. However, it is very important to consider testing artificial intelligence various times before making it public. The impact of artificial intelligence is higher in economic conditions and executes stock trades for different technologies in case of service sector computer algorithms are executing the sufficiently higher role. The artificial intelligence is even creeping into the lives of human beings speedily through scanning machines and GPS navigations.

References of Influence of artificial intelligence

Bigdata-madesimple. com. (2016, 08 18). The future of Artificial Intelligence: 6 ways it will impact everyday life. Retrieved from bigdata-madesimple.com: https://bigdata-madesimple.com/the-future-of-artificial-intelligence-6-ways-it-will-impact-everyday-life/

Blockdelta. io. (2018, 09 19). Artificial Intelligence and its Impact on Daily Life. Retrieved from www.blockdelta.io

https://www.blockdelta.io/artificial-intelligence-and-its-impact-on-daily-life/

Brookings. edu. (2015, 10 26). How robots, artificial intelligence, and machine learning will affect employment and public policy. Retrieved from

www.brookings.edu: https://www.brookings.edu/blog/techtank/2015/10/26/how-robots-artificial-intelligence-and-machine-learning-will-affect

employment-and-public-policy/

Forbes. com. (2018, 03 07). The Impact Of Artificial Intelligence In The Everyday Lives Of Consumers. Retrieved from www.forbes.com:

https://www.forbes.com/sites/forbestechcouncil/2018/03/07/the-impact-of-artificial-intelligence-in-the-everyday-lives-of-

consumers/#cd1e2136f314

Intellipaat. com. (2018, 03 05). How will Artificial Intelligence Impact our Lives in the Future? Retrieved from intellipaat.com:

https://intellipaat.com/blog/how-will-artificial-intelligence-impact-our-lives/

Interestingengineering. com. (2017, 08 31). 17 Everyday Applications of Artificial Intelligence in 2017. Retrieved from interestingengineering.

com: https://interestingengineering.com/17-everyday-applications-of-artificial-intelligence-in-2017

Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Review, 349(6245), 255-301.

Poola, I. (2017). How Artificial Intelligence in Impacting Real Life Every day. International Journal of Advance Research and Development,

02(10), 96-100.

Shabbir, J., & Anwer, T. (2015). Artificial Intelligence and its Role in Near Future. JOURNAL OF LATEX CLASS FILES, 14(08), 1-11.

Totalphase. com. (2017, 05 23). The Impact of Technology in Our Lives and The Future of Technology. Retrieved from www.totalphase.com:

https://www.totalphase.com/blog/2017/05/impact-technology-lives-future-technology/

Villa, F., Ceroni, M., Bagstad, K., Johnson, G., & Krivov, S. (2009). ARIES (Artificial Intelligence for Ecosystem Services): A new tool for

ecosystem services assessment, planning, and valuation. 11Th annual BIOECON conference on economic instruments to enhance the

conservation and sustainable use of biodiversity, conference proceedings.