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The Gender Wage Gap and Artificial Intelligence

The gender wage gap is a persistent problem in the United States and around the world. Women consistently earn less than men for doing the same work. And the gap is even wider for women of color. Closing the gender wage gap is not only a matter of fairness. But it is also critical for the economy and for women’s financial security. The Gender Wage Gap and Artificial Intelligence explores what the technology can do for this issue in depth.

Gender Wage Gap

There are many factors that contribute to the gender wage gap. They include discrimination, bias, and the impact of motherhood on women’s careers. In recent years, there has been increasing interest in using artificial intelligence (AI) as a tool to help close the gender wage gap.

Reducing Bias

One way that AI can help is by reducing the impact of bias in the hiring and salary negotiation process. Many hiring decisions and salary negotiations are subjective, which can lead to bias and discrimination. AI can help to reduce this bias by using objective criteria to evaluate candidates and determine salaries.

For example, some companies are using AI to analyze resumes and job applications. AI is looking for specific skills and experience rather than relying on subjective evaluations. This can reduce bias in the hiring process. It can also ensure that candidates are evaluated fairly.

Analyzing Data

AI can help negotiate salaries. Some companies are using AI to analyze salary data. They then make recommendations for appropriate salaries based on objective criteria such as skills, experience, and job responsibilities. This can help to ensure that salaries are based on merit rather than on subjective evaluations or discrimination.

Automation

Another way that AI can close the gender wage gap is by automating certain tasks and roles. They focus on roles that are traditionally held by women and are therefore undervalued in the labor market. For example, AI can automate administrative tasks, customer service, and other roles that are often held by women. By automating these roles, companies can reduce the number of low-paid, female-dominated positions. They also create more opportunities for women in higher-paid roles.

Career Development

AI can also improve career development opportunities for women. Many companies offer training and development programs to help employees advance their careers. But these programs are often geared towards men and may not be as accessible to women. AI can help to make these programs more accessible by providing online training and development resources that are available to all employees.

Promoting Fair and Equal Pay

Finally, AI can help raise awareness about the gender wage gap and promote fair and equal pay for all employees. For example, AI can analyze salary data and identify pay disparities, allowing companies to take steps to address any imbalances. AI can create educational materials and resources for employees and managers to help them understand the importance of fair and equal pay.

Representation

Leadership

The technology industry is a growing and lucrative field. But it is also heavily male-dominated. Women are underrepresented in the technology industry. This limits opportunities for women and contributes to the gender wage gap. There are many other ways that AI can help to close the gender wage gap and promote gender equality in the workplace. One important factor is the representation of women in leadership roles and in the technology industry as a whole.

Women are underrepresented in leadership positions and in the technology industry. This contributes to the gender wage gap and limits opportunities for women. AI can help to address this issue by promoting diversity and inclusion in the workplace and in the development of AI technology.

For example, companies can use AI to analyze their workforce and identify areas where there is a lack of diversity. This can help companies to identify and address any barriers to diversity and inclusion. And it can help to create more opportunities for women and other underrepresented groups.

Biased Results From Underrepresented Data Sets

Promoting diversity and inclusion is a critical factor in closing the gender wage gap. Also a factor is creating a more equitable and fair work environment for all employees. Diversity and inclusion refer to the representation and inclusion of individuals from different backgrounds, including race, ethnicity, gender, sexual orientation, age, and ability.

AI can help to address this issue by promoting diversity and inclusion in the technology industry and in the development of AI technology. Companies can use AI to analyze their workforce and identify areas where there is a lack of diversity, and they can take steps to create more opportunities for women and other underrepresented groups.

AI can promote diversity in the development of AI technology itself. Many AI algorithms are trained on data sets that are not representative of the diversity of the population. This can lead to biased results. By ensuring that AI algorithms are trained on diverse data sets and that the development teams include diverse perspectives, companies can reduce bias in AI technology and promote more inclusive and fair outcomes.

Having a diverse workforce can bring a range of benefits to an organization. This includes increased innovation, better decision-making, and improved financial performance. However, many companies struggle with diversity and inclusion, and women and other underrepresented groups may face barriers to advancement and equal pay.

In conclusion, promoting diversity and inclusion is critical for closing the gender wage gap and creating a more equitable and fair work environment for all employees. By using AI to promote diversity and inclusion, and by implementing policies and programs to support diversity and inclusion, we can create a more diverse and inclusive workforce and close the gender wage gap.

Flex Schedules: The Gender Wage Gap and Artificial Intelligence

Another way that AI can help to close the gender wage gap is by supporting flexible work arrangements and promoting work-life balance. Many women, particularly working mothers, face challenges in balancing their work and family responsibilities. This can limit their career advancement and contribute to the gender wage gap.

AI can help to address this issue by automating certain tasks and allowing for more flexible work arrangements. For example, companies can use AI to automate routine tasks and allow employees to work remotely or on a flexible schedule. This can help to create a more balanced and equitable work environment for all employees.

Laws and Policies: The Gender Wage Gap and Artificial Intelligence

In addition to the ways that AI can promote gender equality in the workplace, there are also steps that governments and organizations can take to address the gender wage gap. These steps include:

  • Implementing equal pay laws and policies: Many countries have laws and policies in place to ensure that men and women are paid equally for doing the same work. Governments and organizations can work to enforce these laws and policies and ensure that they are effective in closing the gender wage gap.
  • Promoting education and training: Providing education and training opportunities for women can help to improve their skills and career prospects, which can lead to higher salaries and help to close the gender wage gap. Governments and organizations can invest in programs and initiatives to provide education and training for women.
  • Encouraging girls and young women to pursue careers in science, technology, engineering, and math (STEM): Encouraging girls and young women to pursue careers in STEM fields can help to increase the number of women in the technology industry and improve opportunities for women. Governments and organizations can invest in programs and initiatives to promote STEM education and careers for girls and young women.
  • Supporting female-led businesses: Female-led businesses are often underrepresented in the business world and may face challenges in accessing funding and other resources. Governments and organizations can support female-led businesses by providing funding and resources and by promoting initiatives such as mentorship programs and networking opportunities.
  • Promoting flexible work arrangements: As mentioned earlier, flexible work arrangements can help to promote work-life balance and create a more equitable work environment for all employees. Governments and organizations can encourage the adoption of flexible work arrangements by implementing policies and programs that support these arrangements.

Transparency: The Gender Wage Gap and Artificial Intelligence

  • Encouraging transparency: One way to address the gender wage gap is to promote transparency in pay practices. This can identify any pay disparities and allow for corrective action to be taken. Governments and organizations can encourage transparency by requiring companies to disclose their pay practices and by promoting the use of tools such as salary transparency software.

Conclusion: The Gender Wage Gap and Artificial Intelligence

In conclusion, artificial intelligence has the potential to be a powerful tool in the effort to close the gender wage gap and promote gender equality in the workplace. By reducing the impact of bias, promoting diversity and inclusion, encouraging girls and young women to pursue careers in STEM, supporting female-led businesses, promoting flexible work arrangements, and taking other steps to address the gender wage gap, we can create a more equal and fair labor market for all employees.

If you like this article, feel free to check out 8 Ways Artificial Intelligence is Improving Real Estate. Also, 2021 Will Make You Give Drones The Respect They Deserve is a contender for another good read on technology.

SQL

Learn SQL (2021)?

What is SQL?

SQL stands for structured query language.  SQL is most students’ first experience with a database. My first experience was Access.  Before Access, I had an Excel class.  Excel spreadsheets were revolutionary in its time because it organized data when no other program could. I feel like I worked my way up to SQL. They are all methods, created by Microsoft, to organize data.

SQL is the most efficient way to organize complex data. It is a relational database.  All of the information in the database is related. Information is divided into tables and rows. There can be hundreds of tables and rows that relate to one another.  A great example is the database for a mid-sized college. There are thousands of students and these students have classes. The classes have grades attached. Students’ home addresses and phone numbers are also there. These are named and categorized a certain way in the database. There are tables of keys.  We will find foreign keys. There are primary  and composite keys. Also in the chart are surrogate keys. There are natural keys as well.

A very important task to learn with SQL is how to backup and restore. We also have to run or execute queries. These are two important skills to master. There are others of course. However, if freelancing, this is extremely important. A great deal of the requests for freelance help centers around restoration. An example is that a company’s database has been corrupted. They need the database restored without losing any of its data. This is preferable of course. However, if this was not properly handled by the original database administrator, it may not be possible. This is why it needs to be backed up properly the first time. Restores are not problematic afterward.

All That Data

Forbes Contributor Adrian Bridgewater writes the following. “Smart cars and Internet-connected machines are starting to produce huge volumes of time-stamped data.  Companies need to collect and analyze [that] data.” “New software monitoring and measuring strategies have created enormous logs of events that need similar treatment. These trends account for the largest portion of data growth today. The data from these sources always has a core element of time that is crucial to any meaningful analysis. Many enterprises will realize they need a specific strategy for time series data to glean the full value of their business potential,” said InfluxData’s Kaplan.

SQL will handle the above analysis. The statement mentions “enormous logs of events” and that is SQL’s specialty. They will be a huge part of strategy revolved around data in the future.

Data Engineering

“A data engineer works with sets of data to advance data science goals. Unlike other roles, such as a data scientist, a data engineer is not generally as involved in overall strategic analysis. She is more deeply involved in working hands-on with the data sets.” ~ TechoPedia

Sometimes called a database Administrator or DBA, we usually use the programming language Python for scripting. We may also use R or Java.  More coding is involved in data engineering. More calculation is involved in data science.  I have taken a couple of programming classes, and it is encouraged to data engineers. We write the scripts for the data. SQL is the basis and programming is an essential part.

Data engineers work with the life cycle of data sets to help make data useful to a project. Many are primarily interested in aggregating raw data and making it into useful, ordered and structured data formats.” ~Techoppedia

The Pay

The pay is solid.  It is an attraction of the career.  Glassdoor estimates the salary for data engineers in my area, the southest, at 70k-135k.  One can work remotely or at the office.  The freedom is great but the workdays can be long. Coding at a computer on a project is a marathon. It  does not matter if it is to write a program for a database or a website. The end of the project is satisfying and it is a  great relief. Afterward, you will move on to another project if you are freelancing. If working for a company and on salary, monitoring the build will be the job.

Freelancing and salary at a company are the main ways to earn a living using SQL.  However, there is no set industry that we must stay in to use our SQL skills.  We can work in marketing. Paper product companies need past, present and future (or predictive) data to grow. The same is true for the financial field. Market analysis is super competitive and the best tools must be used to get ahead and to stay ahead. Those tools include relational databases.

Growth in the Field

Keep learning and growing in the field. Mentors and advisors constantly remind us. SQL is always evolving and we have to evolve as well. It will take several classes and practice at home to master SQL.  We work on many projects on our own and those of our employers to master the trade.

Growth in this field can take us many places. Artificial intelligence. Machine learning. Data migration. Big data. Internet of things (IoT). These are all subsections of the field.  And they are pretty large subsections.

What are the tools that data engineers work with to achieve data visualization and other hot terms for this field to get comfortable with.  Linux. Hive. Spark. Hadoop. Red Hat. Ubuntu. Power BI. ETL. Presto. Phoenix. Drill. Spark SQL. Data Lake. Azure. Normalization. Query builder. When learning SQL, we should become familiar with these terms. Learning about these with create opportunities and open doors.

Always use a good solid computer for your programming journey. I recommend the following computers.

Alienware 17R4 Intel Core i7-7700HQ X4 2.8GHz 32GB 1TB+1TB SSD Win10, Silver (Renewed)

Alienware Computer

Alienware Computer

Microsoft Surface Pro 6 2 in 1 PC Tablet 12.3″ (2736×1824) Touchscreen, i5-8250U, 8GB RAM, 256GB SSD w/Fingerprint Type Cover, Surface Pen, Dock, Mouse, Backlit, Webcam, Fanless, Win 10 – Black

Surface Computer

Surface Computer

Disclosure: Some of the links above are affiliate links, meaning, at no additional cost to you, I will earn a commission if you click through and make a purchase.

Credits:

Forbes: Adrian Bridgewater (linked above)

Photo by Kevin Ku on Unsplash

Glassdoor.com

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