Category: What’s New in Technology

Technology has greatly contributed to improving and streamlining everyday life. However, as technology advances, there is an increased reliance on digital tools powered by artificial intelligence and machine learning. Unfortunately, these technologies are also challenging the fundamental notion of human agency. As a result, there are rising concerns about humans losing the ability to make independent decisions.

What is Human Agency?

Human agency refers to the capacity of individuals to act intentionally and make choices that shape their lives. Although the human agency is influenced by various factors, including social, cultural, and environmental contexts, individuals should maintain the ability to exert some degree of control and influence over their lives. As far as technology is concerned, individuals must retain control and decision-making power. This calls for technologies that support humans in making informed decisions rather than controlling the decisions made.

Concerns Over the Effects of Digital Systems on Human Agency

The Pew Research Center and Elon University’s Imagining the Internet Center conducted a nonscientific canvassing to gather expert views about the future of the human agency.

The experts were specifically asked, “By 2035, will smart machines, bots, and systems powered by artificial intelligence be designed to allow humans to easily be in control of most tech-aided decision-making that is relevant to their lives?”

Of the 540 experts from different fields, 56 percent disagreed with the statement, while 44 percent agreed. Some of the main themes raised by the experts who disagreed with the statement include:

• The agendas of commercial interests and governments will determine the future.
• The convenience that comes with automation makes users less vigilant over technology.
• AI technology’s complexity and rapid evolution can be overwhelming, making it difficult for users to assert their agency.

Common themes raised by participants that agreed with the statement include:

• Humans also will evolve with technology, and there is the expectation that AI and tech companies will be regulated.
• Expectations that businesses will protect the human agency to retain public trust and to keep ahead of the competition.
• Technology will allow varying degrees of human agency.

Key Considerations for Upholding Human Agency

Seeing that technology will keep advancing and more automated systems will be witnessed, it’s crucial to implement ways to help uphold human agency. Some considerations include the following:

1. Implement mechanisms that contest AI systems. An AI system is as good as the information fed to it. Therefore, it can be faulty or deliberately flawed, and there should be ways to request redress. This can be through AI policies that allow users to contest or rectify a decision made by AI systems.
2. Empower users through systems that include meaningful choices and controls, enabling users to decide how to interact with them. For example, a system should allow users to adjust preferences, customize settings and choose the features they want. This promotes a sense of ownership and autonomy over digital experiences.
3. Promote digital literacy and education to teach about technology capabilities and limitations. Technology users must develop critical thinking skills to exercise human agency and make informed decisions.
4. Integrate ethical principles into technology design and deployment. This can be done by creating guiding ethical frameworks that consider the likely societal impacts and consequences of digital systems.
5. Guarantee transparency and explainability in technologies and algorithms, providing users with accessible explanations of how decisions are made and what data is utilized. This transparency fosters trust in the technology and empowers individuals to make informed choices.
6. Establish accountability for the design, development, and implementation of digital systems. Holding individuals and organizations accountable for the impact of their technology helps maintain human agency and promotes ethical behavior.
7. Implement robust measures to safeguard individuals’ privacy and protect their data. This includes incorporating strong data protection mechanisms, giving users control over their personal information, and establishing clear consent mechanisms for data collection and usage, accompanied by transparent policies. Respecting privacy rights is paramount for preserving human agency in the digital realm.

Conclusion

The essence of being human lies in exercising control over the nature and quality of an individual’s life. However, technological advances such as artificial intelligence are raising concerns about this human ability. Humans are responsible for actively embracing and comprehending the possibilities and implications of living in a world where digital systems take over various tasks and processes. Instead of surrendering their agency, humans should view partnering with these digital systems as a means to supplement and strengthen their intelligence rather than surrendering it.

The internet keeps evolving. It started with static web pages in Web 1.0 before evolving to interactive and dynamic content in Web 2.0. A new phase of technology is now introducing Web 3.0, or the third generation of The World Wide Web. Although it is a work in progress, it is necessary to understand the new concept and how it will impact the future of online interactions.

What is Web 3.0?

Web 3.0 is a term used to describe the next generation of the internet. Industry experts consider it the next big thing in the evolution of the The Web after Web 2.0. Web 2.0 refers to the Internet era characterized by user-generated content, social networking, and interactive web applications; it is known mainly as the Internet of Information.

Web 3.0, on the other hand, is built on top of the existing infrastructure; however, it introduces new technologies that enable computers to interpret data in a more human-centered manner. It combines disruptive technologies such as blockchain, augmented reality, virtual reality, edge computing, IoT, etc. As a result, the internet will become a more intelligent and efficient tool for finding and processing information.

Web 3.0 is also referred to as the semantic web or decentralized web and aims to create a more meaningful online experience by integrating artificial intelligence (AI), decentralized networks, and semantic understanding.

Key Features of Web 3.0

Decentralization

Web 3.0 makes good the move toward decentralization. Decentralization implies that instead of relying on central authorities, data is simultaneously stored in multiple locations. Since Web 3.0 is built on decentralized networks, such as blockchain technology, it creates a more transparent, secure, and trusted web and gives users more control over their data.

Artificial Intelligence and Machine Learning

Web 3.0 will enable computers to comprehend information similar to the way humans do, using semantic web concepts and natural language processing. It also will utilize machine learning – technology that employs data and algorithms to imitate human learning and enhance accuracy. Web 3.0 is designed to leverage the power of artificial intelligence (AI), making web applications more intelligent and enhancing their capacity to make informed decisions. It also helps automate tasks, improve efficiency, and provide more personalized experiences for users.

Ubiquity and Connectivity

The rise of the Internet of Things (IoT) is another contributing factor, enabling information and content to be more connected and ubiquitous. It also means data is accessible via multiple applications and devices.

3D Visualization

Using augmented reality, virtual reality, and mixed reality combined with technologies such as IoT makes it possible to create a spatial web. This helps maintain real-life scale and experience on the web. A good example is the application of VR technology in e-commerce.

Openness and Accessibility

Web 3.0 is built on open standards and protocols, which make it more accessible to both developers and users. This promotes innovation and collaboration across different sectors and communities.

The Impact of Web 3.0 and Challenges

Web 3.0 will significantly change how users interact with information online and transform different aspects of life, including commerce, health, and education, among others. For instance, decentralization gives users greater control over their personal data. This might help limit the collection of data without user consent or compensation.

With blockchain technology as a foundation of Web 3.0, the data becomes immutable, transparent, and hard to hack. This is because all transactions will use self-executing smart contracts.

Web 3.0 will usher in a new era of automation as intelligent systems and algorithms become increasingly integrated into online experiences. This will include more intelligent chatbots, personalized recommendations, sophisticated predictive analytics, and autonomous systems.

As a result, there will be an improved user experience. Users will have a more personalized and interactive experience online, with applications that can better understand their needs and preferences.

Despite the impressive positive impact, Web 3.0 is still in its early emerging stage and is not without challenges. As more significant work and effort are being put toward its actualization, several issues must be addressed. First, to facilitate specific user functions, additional layers must be built on top of the blockchain to ease its complex operations.

Secondly, decentralization introduces data governance and regulation concerns. With no central control of data, bad actors can take advantage to promote hate speech, misinformation and cybercrime.

Thirdly, this new iteration of the internet also requires implementing new technologies and using advanced devices.

Conclusion

The evolution of the internet is inevitable. Although more effort is still required to realize the full potential of Web 3.0, business leaders should be aware of new developments to ensure they can take advantage of opportunities presented by the spatial web and venture into new avenues to remain competitive.

Emerging technologies, such as artificial intelligence, machine learning, data analytics, and biotechnology, greatly transform society and reshape the global economy. However, these technologies also come with a significant challenge regarding ethical and social implications. Global collaboration by governments, regulators, and industry leaders can help ensure that emerging technologies are developed and deployed responsibly.

Challenges of Regulating Emerging Technologies

Emerging technologies have led to complex situations that traditional governments might find difficult to manage. For instance, today’s advanced technologies also come with new forms of crime. This requires law enforcement and public safety organizations to keep up with new and innovative crimes. Today’s governments face challenges that affect the development of effective digital laws.

One of these challenges is the independence of technology from physical state territories. The interconnection of technology devices over the internet has no boundaries. This makes it impossible for any country to regulate all aspects of the technologies. Secondly, all states are not the same, and each enhances its technology-related laws according to its capabilities. While strong economies can afford robust IT infrastructure, other countries do not have the technical capacity.

Other factors that complicate technology regulation include the ability of major technology companies to bypass established regulations. Additionally, states are consumers of technology products and services developed by private corporations. Since they are not innovators, policymakers, and regulators, they do not understand the intricate technology systems that affect the regulatory decisions that must be made.

The above-mentioned are only a few of the challenges that make technology regulation complicated. Still, there is a growing need for digital governance and a digital constitution.

Why Global Collaboration is Crucial in Regulating Emerging Technologies

1. Address ethical and social issues – significant ethical and societal issues, like data privacy and security, are brought up by emerging technology. However, international cooperation can help ensure coordinated and efficient responses to these issues.
2. Growing competition for technological dominance – political, societal, and economic rivalries are driving technological dominance. Increased competition for elements of technology supremacy can only result in conflict, obstructing technology’s ethical use.
3. Technology diffusing globally – in most cases, new technologies are available for adoption anywhere in the world. Thus, international regulatory frameworks must be coordinated to prevent competing or incompatible laws.
4. Harmonizing standards – global cooperation can assist in harmonizing standards and laws for new technology, making it simpler for businesses to comply and lowering entry barriers for new players.
5. Promote inclusivity – emerging technologies have the potential to make existing social and economic inequalities even worse. Collaboration on a global scale can ensure that these technologies are usable by everyone and do not reinforce or introduce new forms of exclusion.
6. Enhance innovation – collaboration across borders can facilitate the exchange of knowledge, ideas, and best practices, leading to more innovation and faster technological advancement.
7. Avoid existential risks – technology can potentially introduce threats that endanger life globally. Such risks might include nanotechnology weapons and engineered pandemics. However, developing strategic global legal frameworks that identify potential risks can help avoid the proliferation of dangerous and harmful technologies.

Existing Efforts for Global Collaboration in Regulating Emerging Technologies

There are numerous initiatives for international cooperation in regulating emerging technologies. For example, the Global Partnership on Artificial Intelligence (GPAI) brings together governments and business executives from across the world. Its goal is to ensure artificial intelligence (AI) is developed and deployed responsibly in a human-centric manner. GPAI’s main focus is on responsible AI, data governance, the future of work, and innovation and commercialization.  

The Organization for Economic Cooperation and Development (OECD) is another international organization where governments work together to solve common challenges and develop global standards. A good example is their recommendation on responsible innovation in neurotechnology, adopted by the OECD Council in December 2019. Other organizations working toward promoting global collaboration and coordination on emerging technology issues include the World Economic Forum (WEF) and the United Nations.

Unfortunately, there is still a lot of work to be done. Continued global cooperation is crucial to ensure that emerging technologies are created and used to benefit society. Currently, there is no global agreement on technology regulation; instead, regulators take different and sometimes conflicting standpoints.

Conclusion

The pace and impact of emerging technologies are likely to keep increasing. Although these developments improve human experiences, the potential for these technologies to disrupt social, economic, and political systems worldwide means that it is essential for governments, private companies, and civil organizations to work together to ensure that they are developed responsibly.

Customer loyalty is critical to any successful business strategy in today’s digital age. With emerging technologies such as the internet of things (IoT), companies are now leveraging a new approach called the internet of behavior (IoB) to gain deeper insights into their customers’ behavior and preferences.

What is IoB?

The internet of behavior exists because of the internet of things. IoT is the interconnection of physical digital objects that gather and exchange information over the internet. On the other hand, IoB makes sense of the collected data from various sources, including wearable devices, digital household devices, human online activity and social media.

The acronym internet of behavior (IoB) was coined by Gartner, a tech research firm, as identified among the top 10 trends in their strategic technology report for 2021. However, the concept of using data to influence customer behavior was developed in 2012 by Göte Nyman, a psychology professor at the University of Helsinki, long before the internet of things took hold.

Gartner defines IoB as an extension of the internet of things, focusing on capturing, processing and analyzing the “digital dust” of people’s daily lives.

Simply put, IoB interconnects IoT, consumer psychology and data analytics. The data is analyzed in terms of behavioral psychology to capture patterns that marketing and sales teams can use to influence customer behavior.

How IoB can Influence Customer Loyalty

Aside from products and services, customer experience has become a significant factor in business success. By understanding customer behavior, businesses can leverage IoB data to influence customer loyalty in various ways.

Personalization

Personalization has the power to transform customer experience. This is reflected in a survey that revealed 76 percent of Americans are more likely to complete a purchase because of a personalized experience.

To take advantage of IoB, companies study insights extracted from collected data and use it to decipher customer behavior; that is, their practices, preferences, habits, needs, wants and more. The company can then leverage this data to offer personalized product recommendations, such as insurance premiums, saving plans, travel destinations, etc.

For example, an insurance company can have users install apps on their phones that collect data on distance traveled, car speed, etc., and optimize their car’s premium based on driving behavior.

Timely Improvement of Products and Customer Services

IoB also makes studying how customers interact with specific services or products easy. This saves companies from time-consuming surveys that are used to determine consumer preferences. The collected data is analyzed to identify pain points and issues of concern. The company can then address the issues before they become significant problems, such as by improving on products and services. This is an excellent way to build trust and confidence in a brand, leading to customer retention.

Behavioral Retargeting

Since companies can access customer preferences, recent activities, likes, dislikes, and location data, they can send real-time notifications to customers about discounts and new offers in stores nearby. They also can track loyal customers and offer them rewards. This kind of retargeting will make customers feel like a business values them and caters to their interests.

Develop a Tailored Marketing Strategy

Insights from IoB data can help tailor marketing strategies to individual customers. For instance, a retail store can offer products or services based on the mood, age or gender of a customer; thereby providing a satisfying experience that will lead to a stronger emotional connection with the brand.

Key Challenges that must be Addressed for the Success of IoB

Despite the opportunities IoB offers, companies must be aware of some key challenges to fully realize its benefits.

• Privacy Concerns – Although personalization will make consumer lives easier, there is a concern about privacy. Companies must implement strong cybersecurity policies and measures to ensure that customer information is used only for that which a customer has given consent.
• Convincing Users to Share Personal Data – People might not be comfortable sharing their personal data.
• Laws and Regulations – Strict regulations around collecting and using personal data, such as the General Data Protection Regulation (GDPR), require companies to comply in order to avoid fines and legal issues.
• Cybersecurity – As reliance on technology rises, so do cyberattacks. Cybercriminals may access sensitive data on consumer behavior, making consumers susceptible to online scamming and identity theft, among other threats.

Conclusion

Leveraging IoB can provide businesses with a competitive edge and drive revenue growth. Companies seeking continuous success should consider placing IoB at the center of business innovation to create personalized customer experiences. At the same time, they must also examine any challenges that might reduce the effectiveness of IoB.

Natural language processing (NLP) is a technology that allows computers to understand and process human language. Processing of natural language is necessary when you want an intelligent device to follow your instructions. NPL is an artificial intelligence (AI) component with many real-life applications.

As technology advances, business leaders have to figure out how to tap into the new trends to remain relevant, stay ahead of competition, and meet consumer expectations and needs.

How NLP Works in Brief

NLP involves making computers perform tasks with the natural language humans use. The input and output can be spoken or written text. NLP combines computational linguistics – rule-based modeling of human language – with statistical, machine learning, and deep learning models.

NLP aims to build machines that understand and react to text or voice data and then respond with text or speech in a similar manner as humans do. Examples of NLP in real life include voice-operated GPS systems, personal assistant apps, speech-to-text dictation software, and customer service chatbots.

As businesses seek better ways to improve efficiency, NLP is one technology promising huge rewards for enterprises dealing with vast quantities of unstructured text. In accounting, unstructured data include transaction descriptions, invoices, written communication, etc.

The use of NLP is growing significantly in enterprise solutions designed to help streamline business operations. Large companies such as Deloitte, Ernst & Young (EY), and PricewaterhouseCoopers (PwC) have implemented various NLP solutions. A good example is Deloitte, which incorporated NLP into its Audit Command Language to improve contract compliance.

How NLP Can Improve the Efficiency of Accounting Processes

Areas in which NLP helps improve efficiency include:

1. Forensic Investigations
   When CPAs want to perform forensic investigations, they have to deal with significant amounts of data from documents such as bank statements, transaction data tables, and data found in emails or deposition transcripts. Analyzing all the data as they try to look for specific patterns or gain insights is challenging. However, the application of NLP can be helpful in the investigative analysis process. NLP using algorithms can identify patterns automatically and reduce the time it would have taken to analyze the documents.
2. Accounting and Auditing
   Auditing is challenging due to the process of reviewing financial statements and ensuring they match regulations and legal standards. Auditors must have excellent analytical and decision-making skills to spot inaccuracies in financial statements. However, NLP helps to optimize the auditing process.
3. Financial Analysis and Automated Generation of Financial Reports
   NLP can automatically extract financial data from balance sheets, income statements, and cash flow statements. This can cut down on time and error-prone work. At the same time, it can obtain insights from massive financial data sets and financial reports. This enables accountants to make data-driven decisions and quickly identify trends and patterns in the data, hence, making it easy to provide guidance to clients on investments and household finances.
4. Automated Data Entry
   NLP can be used to extract data automatically from unstructured text documents, including bills and receipts. It also can be used to automate the entry of data from tax documents and input it into accounting systems. This can cut down on time and error-prone work.
5. Improve Centralized Data Management Solutions
   Incorporating NLP in accounting and procurement helps improve the ability of a centralized data management system to collect and integrate data from different sources. This enables standardization and collaboration. Additionally, the data provided has higher-quality insights. As a result, there is better financial planning and improved risk assessment and management.
6. Customer Interaction
   NLP can be used to enhance the effectiveness of customer interaction. This is done by automating the procedure for responding to client inquiries, such as concerning invoices, payments, and account balances.

Conclusion

Natural language processing is proving to be a powerful technology that can help improve the efficiency and effectiveness of accounting processes. As it continues to evolve, it will likely become an increasingly important tool for accountants and other financial professionals. Most importantly, these advanced technologies take care of manually reviewing unstructured data. This helps businesses scale and – at the same time – reduce costs.