Chapter 15: Business Technology Advancements

What We’ll Cover >>>

• The Future in Business Technology
• Home Automation
• Workplace Automation
• Artificial Intelligence
• Hardware
• Software
• Access to Technology

The Future in Business Technology

This textbook has covered a lot about computing, productivity, and the Internet. It might be hard to recognize what that all has to do with business technology, specifically.

As covered at the beginning of this book, Business technology refers to the technologies and systems that help employees accomplish activities. It is related to use in school and the workplace, and includes computers and their peripherals, software and utility programs, and systems/use of the Internet. Business technology is about all the uses that make finding and getting a job, getting the work done, and providing results for stakeholders like customers, vendors, shippers, colleagues, and students.

All that this book has covered has been supporting information and reference to issues and challenges that support business technology. Often the technology discussed wasn’t specific to the workplace (sometimes school, sometimes behavior, sometimes general technology). However, in one way or another the business/work market is impacted, because we as students, prospective employees, and actual workers are impacted. Essentially, there are aspects of technology / the digital world that can’t really be separated from the core definition of “business technology”. It is all inter-related.

This chapter will discuss current and possibly pending advancements in technology, which in one way or another is inter-related to the business world.

Home Automation

Home automation impacts the business world because it is a series of products and services, because information privacy and security are part of the equation, and because more people work in home offices that are affected. Employees in this business market are responsible for the development, assembly, and management of the products, as well as the technical and customer-service support.

MedAttrib: technofaq.org CC BY-NC-SA 4.0. Image of smarthome.

Initially, most people’s home networks had just a few connected devices, like a computer and a printer. This has changed in recent years. An important need is to keep firmware updated, and consider a 2nd Wi-Fi network so that computers/work assets don’t mix with the smart home.

Smart Devices

Home automation allows many devices to connect to our home network. Typically, these “smart” devices work just like their regular counterparts, like light switches, and they also have programmable smart features. They allow for tracking usage of power/energy, and by people who have access. They can help automate some chores. Programming can happen on the device, by smartphone, and by voice.

• Smart Appliances. Get reminders if something is finished with a process, like the washing machine or oven. Set the coffee to brew before you wake up. A smart fridge can let you know food is spoiling, keep a shopping list and deliver it to your smartphone, and narrate recipes. Smart ovens can preheat and turn off with the recipe instructions.
• Smart Lighting. Smart wall light switches work like a normal light switch, but can be turned on or off using your computing device. They can be programmed to activate the lights at certain times. Smart light bulbs are similar, but you leave the old light switch always turned on, and turn the smart bulb on and off through the app or a secondary switch.
• Smart Locks. A keypad can be programmed with a specific code, including ones for different people to track use. The door can also be locked and unlocked from a smartphone app.
• Smart Smoke Alarms. A low battery can prompt a reminder message before the alarm goes off.
• Smart Speakers (with microphones). Don’t want to use your phone or your watch to control your home automation, then give it a voice command instead. “Answer the phone” when it rings, or just to “Set the timer for 3 minutes” are just two of many possibilities.
• Smart Thermostats. This can be programmed for temperature ranges at different times.
• Smart TVs. Video streaming services such as Netflix provide on demand access to movies, documentaries, etc. A smart TV will have apps to access common streaming services, and also allow you to connect your phone or computer to the TV so you can view your photos or computer screen on the larger TV screen.
• Video Doorbells. The doorbell can notify your smartphone, and display the visitor. You can talk with them, and consider the tool as a security system that takes a picture of whoever comes in range of the doorbell’s camera.

Workplace Automation

Workplace automation uses technology systems to do repeatable / predictable workflows without requiring manual intervention. The technology systems are a blend of artificial intelligence (AI), machine learning algorithms, and robotics. Programmed effectively and correctly, automation can improve efficiency, reduce repetitive motion injuries, minimize human error, and support customer interactions that require standard information.

We already experience many of these uses when visiting websites and needing customer support. The key to making this workable is it put the customers first. The digital interfaces have to be well programmed to really be responsive and be able to resolve most problems, so that a customer can get rapid assistance and ask for a live person only when needed.

Uses of workplace automation

• Asset tracking: Digital tags can also be applied to warehoused products, to automate tracing, reporting, and ordering.
• Automated Data Collection: This cab be configured to generate data entry input forms for a customer to use online, and/or for a phone customer’s call responses to be translated into a form and added to a database. Once in the database, the data can be sorted, analyzed, scheduled, and acted upon, with tracking and documentation.
• Customer Relationship Management: Some or most of customer management – depending on the business – can benefit from have automated problem-solving options. Customers can experience a CRM digital voice on the phone or a digital assistant on a website chat. They can receive bot-scheduled return calls to avoid waiting on hold. The live person can pull up database information to verify the customer’s identity and follow up on the problem resolution.
• Digital tracking: Using digital tags and electronic shelf label can allow for the automatic syncing and updating of pricing, and update in-store inventory’s stocking needs.
• Human resources: Recruiting can be done with attaching a database-reading application form onto job listings. Applicant data goes into the database and is there for tracking through the process: initial phone calls, comments, interview, and hiring process. Trainings can be assigned for onboarding, and some trainings can be automated digital scenario-based programs. Scoring, plus employee accomplishments and annual reviews go into the database.
• Industrial automation: Heavy, body-stressing, small-space, and detail-oriented work on an assembly floor can be assisted by robotic counterparts. An example would be Boeing (because the author temped at the Everett plant and daily watched the assembly line). Boeing now uses an automated drilling system for plane exteriors, and a robotic painter for the 777 wings. Other examples in industry could be machining, welding, and other metal fabrication work.
• In-person support: An office that has rare customer visits and does a lot of online work might not need a fully staffed front desk reception all day long, which can allow job sharing or only 3-4 hour in-person reception.
• Managing financials: A lot of a company’s financial work can be automated. Online forms can let employees input expenses that need to be reimbursed, timesheet info, vacation hours, etc. Payroll just needs access to timesheet data to auto-process salaries and deductions then and deposits.
• Marketing automation: Much of the acquisition of customer data is about being able to personalize marketing plans and advertising techniques. Bulk ads and print ad campaigns aren’t cost-effective and tend to be one-size fits all. For lower cost, through automation and digital delivery, prospective and repeat customers can be targeted with personalized ads, deals, discounts, and preferences. This is already common on Amazon and other sites.

MedAttrib: technofaq.org CC BY-NC-SA 4.0. Relationships management.

Artificial Intelligence

Artificial intelligence is a lot more routine than we may think it is. People have memories of the Terminator film regarding AI, robotics, and ‘Skynet’. However, at this time most AI is about programming algorithms to apply to bots, computer systems, and some people-facing automation tasks. This book doesn’t have the bandwidth to devote sufficient time and space to what is happening even now, and other articles/books will be popping up all over that will cover every aspect of AI as it develops and moves forward. However, it is worth some coverage, given that in the past couple of years we have been learning more about, and been given access to, generative AI use. It is poised to affect and transform many of our basic computing, business technology, and information technology realities – as well as impact our sense of information integrity and personal privacy.

Basics of AI

Artificial intelligence is the development of computer systems able to perform tasks that normally require human intelligence. It requires a computing device to be able to learn through experience to expand on basic programming. This is what ‘deep learning’ and ‘machine learning’ refers to: a method of teaching computing devices to recognize complex patterns things like language, images, and other data to produce accurate insights and predictions. Software algorithms are able to learn and become better at carrying out specific tasks as they are exposed to more data that helps them refine and limit the need for repetitive input by the user because the AI adapts to the input and integrates it into future use.

• Machine learning: AI programming that can automatically adapt with little human interaction.
• Deep learning: Artificial neural networks mimic the learning process of the human brain.
• Foundation model: AI training on massive amounts of data with different sensor modalities to be able to perform a variety of tasks, rather than being designed for only one purpose.

Applications are can include:

• AI with language and pattern-recognition training will become better at detecting plagiarism, cheating, and other patterns in social and education output.
• AI with sufficient exposure to big data and case studies can research and identify diseases more quickly and accurately, and streamline drug development.
• Conversational search, which would allow a dynamic conversation with an AI to produce specific search results.
• Decision-making, approving a job applicant for an interview, or determining qualifications for unemployment, etc.
• Predictions (outcomes inferred by big data analysis). An example would be climatology.
• Robotaxis may become a common transport option given that driverless cars have moved so far in research and development.

MedAttrib: L.J. Bothell image of “Artificial Intelligence in College” generated from DeepAI generator. (yes, I planned on the irony here, just to demonstrate. :0) )

Issues in AI

On September 26, 2023, your author (Mesozoic age), who uses MS Windows 11 on a laptop, received another Microsoft update. This update included a rollout of MS Copilot, (Preview) which one would like to think is a new version of what MS Cortana and the old MS Clippy paperclip bot used to be. However, it is expected to be much more, and is an “AI companion” that is fully integrated into Microsoft products/apps.

Now, one doesn’t need to go look for and sign-up to use ChatGPT, Dall-E 2, and a bunch of specific AI tools for specific uses like creating art, turning legalese into straightforward language, cleaning up audio, etc. One can just click the Copilot icon and a window pops up to allow you to choose a conversation style for your input, and ask it anything. Say I ask it “how long do Tabby cats live?”, I get a response that the AI draws from aggregated information on the Internet. Interestingly, the response added small footnote hyperlinks so I could click and see the source material, which is an approach to offering information integrity and attribution. The same question posed to ChatGPT did not offer links or attribution information. Dall-E 2 requires one to purchase ‘credits’ to use it, so I did not ask it.

AI Accessibility

This little exercise in just getting a Microsoft update reveals several things about AI in general:

• A push for AI companion use tied to an OS (implying use of your whole computing experience and computer data to for the AI to access for workflows)?
  • The MS Copilot as a preview is free, but currently seems designed to be for Enterprise users (corporate paid account use, like at colleges, companies, etc.). It may also be available for consumers of MS Office 365 for $30/month (as of 9/23).
• Copilot does offer the approach to attributing source information for the user to see where the data is referenced.
• Another approach (ChatGPT) requires you to set up a currently free account to start using it (implying your consent and use of your information). It does not seem to attribute the generated information so it could come from anywhere, including inaccurate or wrong information.
• Another approach – called an Open Source tool, seeks to monetize even before you can use it.

Overall, whether paid or not, whether needing an account or not, the AI tools are being designed so you can input a question or ask for some kind of process/product, and get a varying degree of responses and results, depending on how the AI tool is designed and the algorithms it is programmed with.

AI Uses of Concern

Research starter: You can type in a question and the AI can generate a response. This is a step beyond just Googling something and getting a list of links to check out. The AI does the aggregation work and responds back. The issue can be if the user doesn’t really understand the information in depth, which affects the information integrity, the attribution/citation of sources, and mostly copies/pastes the response in lieu of personalized learning in job and academic situations.

Workflow integration: According to the goals of the Microsoft Copilot, you can also streamline your workflow across applications. It promises to (paraphrase here) “comb-sort across your ‘entire universe of data at work’ and the web, and have a ‘deep understanding’ of you and your job/priorities/organization to a head start on . . . complex or tedious tasks”. What will this mean? It may mean taking various notes you have kept on a work process or subject, and pulling it all together into a single document so you can decide what to use. It may mean the creating of AI-enhanced or designed images using MS design tools. It may mean personalizing information for you for shopping, planning an event, preparing a report, etc. It may help with predictive analytics from  your Excel workbooks and database information, and other programs you use. It also may mean that nothing on your computer that can be reached by the AI app is private or fully secure, especially you don’t know if the information shared to the Cloud is truly yours, the employer’s, or somehow considered nobody’s because the AI generates from it.

Automation of repetitive tasks: Sorting through surveys or data to summarize specific information will become easier and, as the AI learns, more accurate. It can check code, review resumes, check digital inventory information for needed ordering, etc. Depending on the algorithms used and the human oversight, this can be very useful or allow for information bubbles that leave out important considerations when decisions are made.

People Management: AI is seen as a very useful way of assessing customer and employee information in order to personalize experience, market more efficiently to specific demographics, determine the viability of products, build contact lists, identify needs, and streamline workflow and costs. In the workplace managers can see who is thriving, who needs training, what the workplace needs are related to the number and type of employees, etc. However, people management by algorithm alone is a risk, especially if it is part of one’s heathcare, one’s employment, ones banking/finances, and so on.

• For instance, various Global 2000 companies use ‘digital managers’ which allow workers to be be hired, have pay and benefit disparities, be compared statistically against other employees, and be fired by algorithms – without any human intervention or contact/follow-up with the employees.

Data analysis: AI will be able to scan vast amounts of data for trends, incongruities, and specific criteria, faster and more accurately than humans in data analysis positions. AI might also, depending on the algorithms, be able to support or make decisions from the data analysis, such as for marketing, job candidates, and employee success/failure. Consumers will be able to refine and personalize their needs for information from a much larger bank of data with more accuracy and efficiency. Vast data analysis can be very useful; algorithm/AI-based decision-making may be problematic if there isn’t sufficient human oversight and redundancy to get past the ‘process’.

Product creation: Generative AI, in giving responses to questions and prompts, are being used to write actual research reports, executive summaries, articles, emails, essays, stories, and more. AI can also generate digital art, music, video, etc. Instructors are recognizing that students. The tool is “supposed to be” used responsibly, such as for idea prompts, research collation, creativity for fun, etc. It can be used for generating suggested outlines of content for a paper, find sources, help draft your own information into resume formats, and make an illustration example of an idea you are trying to communicate or a small soundbyte for a website you want to attach a personalized sound effect to.

• In academics, teachers are seeing more situations of students relying on generative AI for composing the bulk or entirety of their assigned coursework. Teachers can expect students to use AI to generate essay and project ideas, help them find sources for their research, generate a structural outline based on a project’s available information, and maybe even help refine out redundant content that would bloat an assignment. Teachers themselves may use AI tools for brainstorming and streamlining assignment ideas.
• However, AI can be a problem when students cheat with it by using full content instead of doing their own work. Why? One, cheating/plagiarizing is unacceptable in any case, since the student clearly doesn’t learn the content and attempts to apply it to the real world and on a job – like as a nurse with medications, a mechanic with working trucks, a graphic artist with a cheat portfolio, a psychologist interfacing with people’s mental health – is a lie. However, with generative AI, it steps up to worse when AI content sourced from multiple creators has no attribution/citation information, and when one can’t even trace where the information came from. Does it have currency, relevance, authority, accuracy, and a specific purpose? Or is it hearsay, chatbot-based, social-media, slanted, or worse – using the copyrighted intellectual property of others without license or payment?
• This problem persists when consumers use generative AI to create ‘stories’. “artwork’, ‘music’,, ‘news articles’ or other seemingly personal ‘intellectual property’, then pass it off as their own original work while trying to profit and create an artistic reputation. Does it copy the work-style of specific music artists, or slander a public figure, or ‘look’ like a Monet or H.R. Giger, or a Jane Austin story, or a James Cameron script?
• This problem also allows publishers of various media (written, music, film, photography, visual) to try to replace human creatives with generative AI content in order to avoid giving credit, negotiating fair and appropriate use, and paying salaries, royalties, & licensing fees.

As you can see, AI is a growing tool, benefit, workplace need, and issue full of unfolding problems, concerns, and ways to continue evolving. Definitely for other books and articles to cover!

Hardware

How is computing hardware progressing? The discussion in Chapter 2 covered the basics of how things work; what’s coming up?

We’ve been accustomed to the Moore’s Law that every 2 years the processing power we can pack into a square inch doubles. That is how we moved from room-sized supercomputers to small and slim smartphones that can do almost anything.

Now, the research and development process is moving away from silicon-based transistors made from materials like graphene. Deep-learning software is enhancing programming and responsiveness. Noises are being made about quantum computing: moving from standard bits to quantum bits (qubits) , which can surpass standard binary 0 and 1. My brain can’t handle it, but the results could allow a quantum computer to find solutions in fewer steps than a standard computer, which would speed up processing. The quantum solution wouldn’t necessarily replace existing computer technology, but supplement is with an additional specialized chip.

A survey of Google results for various “future computing” keyword phrases suggests:

• Battery improvements: R&D is being done to create longer-lasting batteries that don’t need as much recharging, and using materials with lower environmental impact.
• Chip advancements: To develop more efficient and cost-effective chips, the industry is working toward imprinting learning algorithms on chip architecture as another example of AI.
• Computing input/Holographic tech: Touchscreen capacity is being researched to develop predictive touch, which would rely on machine learning to predict user actions. Holographic virtual tech is working to create line-of-sight 3D images the need for glasses / interfaces. This could accelerate the possibility of holographic screens and allow for air-sweeping motion.
• Distributed computing: Multiple computers work by sharing their computing power. A network would behave as a single computer that provides large-scale resources to deal with complex problem solving.
• Energy costs: Technology – the development of computing devices, and the management/operating of vast server data centers (power, cooling), will have to be dealt with. Greening data centers to get to net zero emissions and 100% efficiency is underway; however, significant progress will need to be made to repurpose generated heat for the grid and for much more energy efficient equipment.
• GPU dominance: Graphical Processing Units (GPU) co-work with the Central Processing Unit (CPU) on computers. The GPU’s purpose is to enhance computing with parallel processing to handle a lot of workloads at the same time. Big graphics, CAD, and gaming have been the beneficiaries; GPUs are also being tasked with training artificial intelligence (AI) and deep learning models. GPU performance will have to evolve rapidly, and in time they may supplant the CPU.
• Neuromorphic technology: Elements of a computer hardware and software elements are modeled after systems in the human brain & nervous system. This could allow devices to search for new info, learn, retain data, and make deductions.
• Scalability: A goal of computing is to increase the scalability of processing, harness the resources of multiple machines, and make cloud environments “agnostic” – independent of being designed for specific computing architecture and instead being able to serve any device. This in turn may cause a shift in hardware acquisition itself. Currently we have software-as-a-service (SaaS) with subscription software like MS Office. Computing hardware may undergo a similar path, with organizations moving away from requiring large expenditures on equipment and instead leasing hardware-as-a-service (HaaS).

Software

How is computing software progressing? A survey of Google results for various “future computing software” keyword phrases suggests:

• Application programming interfaces (API): An API is a software interface that helps developers link cloud computing services which make data/computing multifunctional for numerous programs. This allows data from isolated locations to be pulled and harnessed.
• Augmented reality: This will continue to be developed to reach personalized immersive experiences with tethered and standalone devices. Immersive experiences will need a huge push for 3D assets, and generative AI will be able to accelerate this.
• Blockchain-oriented software: Through a blockchain database process, data in systems is replicated, closed in a set called a block, and decentralized. Blocks are lined in a chain (blockchain) which, with transaction recording and public-key cryptography, ensures data security. Data can be viewed but not modified or hacked.
• Continuously deployed software updates: Code changes to an application are automatically tested and released automatically into the production environment. Version control, code review, and configuration management helps bypass the need for quality-assurance testing and human approval.
• Cybersecurity applications: With expectations of growth in cybercrime, like ransomware, AI /machine learning is being applied to security automation software. Software will have to become multifunctional to accommodate cloud security, IoT devices’ security, and the unique challenges of blockchain coding.
• E-commerce platforms: A content management system (CMS) and commerce engine that webstores use to manage products, purchases and customer relationships. Future improvements will need to blend user-friendly web presences with support for IoT, voice, and augmented reality aspects of e-commerce stores.
• Low code development: Low-code allows the creation of coded applications without needing developer skills, because a visual UI allows drag & drop pre-made code blocks. IT support will still need to supervise and test the results, concerns include security and ability for the apps to integrate with other business functions.
• Microservices: The process of monolithic architecture, in which application processes are grouped and handled as a single service, is having to be updated because grouped code needing complete app changes is not agile. Microservices architecture modules are built as independent services that use API communication. Modules can be built, managed, and changed independently of the others, can be scaled easily, and be reused in other projects.
• Multi-model databases: A database management system that organizes many NoSQL data models using a single backend, a unified query language, and API. There is a growing trend toward databases offering many models and supporting several use cases. Different than relational databases because different data models from diverse databases can be queried and combined with a specific query language.
• New computing languages: New programming languages are being developed to solve problems like speed optimization, scalability, and a need for user-friendly learning curves. Pluses in a language include being “memory safe,” or able to translate into and secure JavaScript syntax, or being hybrid like F#, or having early code-error detection.
• Online marketing: Like other software development plans, online marketing platforms are increasing reliance on augmented reality, AI, chatbots, and other digital tech. Omni-channel experiences are being promoted in order to improve customer retention; a customer should be able to expect the same experience in a store, online marketplace, social media, or by phone.
• Progressive Web Applications (PWA): PWAs work are coded with HTML, CSS, and JS like websites without a browser interface or a need to download. They are platform agnostic for mobile, tablet, and desktop computing. Examples include retail storefronts, social magazines, game apps, etc.
• Sharing Economy: Collaborative consumption platforms connect users with suppliers in real-time with GPS, data analytics, and AI. Focus is on personalized experiences, security, and the use – not ownership – of products and resources. Uses include crowdfunding, lodging, transportation, co-work spaces, and goods recirculation.

Access to Technology

A constant challenge is access to computing tools, the Internet, and efficient connections that provides security, speed, and no interruptions of service.

Part of the issue, as previously discussed, is a limitation of infrastructure in various regions in the U.S. and various countries around the world. Another issue is cost, for subscriptions to broadband service and for equipment that can do the work needed in education and workplace contexts. Another issue – which is outside the scope of this book – is standardization of services, as was recognized in education during Covid. Different workplaces – even branches of the same company, might have a lack of standardization of employee resources and management platforms.

Connectivity

5G: Now being rolled out and promoted is 5G, another generation of mobile networks. 5G is expected to have lower latency, which should effectively support AI, IoT, and augmented reality. It promises faster download speeds than the current 4G, which could improve video conferencing and automated tasks than at present.

Interconnectivity: Distributed IT infrastructure of many companies will be using hybrid-cloud or multi-cloud platform. Data and processing will be managed in the cloud although may be accessible to devices faster. More web platforms will be multifunctional and reliant on this interconnectivity so that companies can keep costs low, productivity high, transactions and data highly secure, and customer relations personalized.

Digital accessibility: Everyone, including persons with divergent needs, needs full access to digital content. Accessibility standards processed by usability engineers need to be personalized and applied to computer interfaces. The goal needs to be Universal Design, which would remove most or all barriers altogether, rather than just behaving as assistive technology. This goal still seems distant, although AI and robotics in web platform usability could offer significant advancement, especially since the continuing increase in technical layers can be off-putting to users with divergent capabilities.

Some emerging accessibility benefits include:

• Improved voice-to-text functions.
• Connecting with a virtual assistant.
• Smart home functionality.
• Assistive technology tool Morphic that personalizes the computer to a user’s needs.
• Possible public access bots/interface add-on that could assist a variety of accessibilities.