As COVID-19 has imposed social/physical distancing on business and individuals alike, businesses are looking for digital solutions that enable contact-less commerce and remote work operations amid this global pandemic. Chatbots are the answers to many challenges posed by the pandemic, from social distancing to increased volume of customer/employee queries to remote working.
Chatbots add immense value to businesses not only in service quality, delivering it scale and speed. In the current COVID19 pandemic, businesses across industries are using them in a variety of ways to help their employees, customers, clients, partners, vendors, and other stakeholders.
Here, I am listing out some popular use cases where Chatbots can help during COVID-19:
- Telemedicine: The healthcare infrastructure is strained as healthcare workers are struggling to cater to the huge influx of COVID-19 infected patients, coupled with the fact of a dire shortage of essential medical resources not being met by the supply-side due to lockdown. Patients with other medical issues are postponing their care visits to reduce the risk of virus infection, in effect, drying up the other revenue streams for healthcare institutions. The adoption of telemedicine has increased as a result to counteract it. Chatbots can monitor and track the health conditions of home patients and provide a medical diagnosis to self-care patients. In case patients need critical care, they can alert the hospital/doctor to provide emergency rescue measures. Chatbots can also relieve overburdened doctors by assisting doctors with patients’ symptoms tracking, medical analysis, and treatment recommendation.
- Virtual Appraisals: COVID-19 is having a tremendous impact on fleet management and insurance companies. Due to the stringent lockdowns and safety concerns, field appraisers may not able to do home and field visits to perform physical inspections for claims processing. A Chatbot for virtual appraisals can enable Photo-based Estimations for faster and Safer Claims Processing without waiting for in-person damage assessment. Read our case study to learn how Unvired helped a Pennsylvania based Fleet Management Company to complete virtual vehicle damage assessment and appraisals without the need for a driver to go to the repair body shop or interact at close quarters with an appraiser in the field.
- Order Health Supplies: COVID-19 has brought new challenges for fleet management companies to ensure driver and customer safety. They need to comply with strict guidelines for vehicle sanitation. A Chatbot can help drivers order health supplies (like masks, sanitizers) directly from the vendor or the company online store. Using the same bot, they can claim reimbursement for purchased items by submitting a picture of bills/payment receipts for approval.
- Return to Work Guidelines/Checklists: As businesses reopen and employees return to work, state authorities have defined strict guidelines for adherence to prevent the spread of COVID-19. Chatbots can be very effective in answering COVID-related FAQs and employee queries, performing safety and risk assessment checklists, sending alerts, and more.
- Customer Service: Nationwide quarantines, movement restrictions, booking cancellations, and business uncertainty have generated high demand for customer service. The soaring incoming volume and reduced staff capacity have already increased the higher wait time. As a result, organizations are rushing to implement Chatbots to improve customer reach and experience. A bot can answer a bulk of simple and repetitive questions that save time for support staff to focus on high-value calls.
- IT Helpdesk: The success of remote working hinges on the capabilities of the IT team. In addition to ensuring adequate communication infrastructure, document management system, productivity tools in place, the team has to deal with round the clock support for remote teams to enable work continuity. For IT teams, Chatbots can play an integral part by providing 24×7 service availability in the instance of device malfunction or outages. When connected to the knowledge management system, IT helpdesk Chatbots can deliver instant answers for both technical and end-user queries. Chatbots can also be used to perform simple but critical functions of password resets, notifications, and help raise issue tickets for human intervention.
- Human Resources: Remote working has been the response of businesses to lockdown, in effect overburdening human resource teams to provide Work from Home facility. Chatbots can help HR teams in many steps of this workplace transformation. It can automate a huge volume of simple yet persistent queries on workplace guidelines, employee policies, leave requests, PTOs, salaries, and more. HR can leverage Chatbots to ease the monumental task of the eventual return of a large part of the workforce to the office. Recruitment during a pandemic is another aspect in which Chatbots can play a key role in HR processes, automating employee orientation, and onboarding, which consist of a substantial amount of queries to the HR team.
- Procurement: Procurement has been forced to evolve rapidly from the onset of COVID-19. The span of the pandemic across multiple geographies has put near to mid-term purchase plans into jeopardy. Chatbots can perform as a critical digital lever for procurement professionals to handle disrupted supply bases and form a viable alternative to engage with suppliers. During social distancing, Chatbots provide an important interface to help purchasers in guided buying and make purchasing decisions. Information such as product availability, contract terms, shipment status, supplier status, pricing details, outstanding amount, and purchase history can be obtained using Chatbots.
Unvired is a Digital Solutions provider of mobile/web applications, digital forms, and artificial intelligence-enabled Chatbots for Enterprises. Unvired has developed a Bots platform Chyme, On top of which, virtual/digital assistants for IT help desk, customer service, FAQs, sales, marketing, and procurement have been built. Chyme powered bots are omnichannel and can be invoked from Slack, Skype for Business, Facebook Messenger, Facebook Workplace, Google Assistants, and others.
Using embedded analytics in software applications can drive your business forward
Analytics in your tools can help users gain insights that can help move your clients and the organization to the next level.
More than two years ago, Edsby, which provides a learning management system for educational institutions, began embedding analytics into its software that enabled teachers and administrators to detect student learning trends, assess test scores across student populations, and more, all in the spirit of improving education results.
The Edsby example is not an isolated event. Increasingly, commercial and company in-house software developers are being asked to deliver more value with their applications. In other words, don’t just write applications that process transactions; tell us about the trends and insights transactions reveal by embedding analytics as part of the application.
“Software teams are responsible for building applications with embedded analytics that help their end users make better decisions,” said Steve Schneider, CEO of Logi Analytics, which provides embedded analytics tools for software developers.” This is the idea of providing high-level analytics in the context of an application that people use every day.”
SEE: Microservices: A cheat sheet (free PDF) (TechRepublic)
Schneider said what users want is transactional apps with built-in analytics capabilities that can provide insights to a variety of users with different interests and skill sets. “These are highly sophisticated analytics that must be accessible right from the application,” he said.
With the help of pick-and-click tools, transaction application developers are spared the time of having to learn how to embed analytics from the ground up in their apps. Instead, they can choose to embed an analytics dashboard into their application, or they can quickly orchestrate an API call to another application without a need to custom develop all of the code.
“You can just click on the Embed command, and the tool will give you a Java script,” Schneider said. “In some cases, you have to do a little configuration for security, but it makes it much easier to get analytics-enriched apps to your user market faster.”
Getting apps to market faster
Here’s how an embedded analytics tool can speed apps to market.
A marketing person is tasked with buying ads and organizing campaigns. He or she gathers information and feeds it to IT, which periodically issues reports that show the results of ad placements and campaigns.
SEE: How to overcome business continuity challenges (free PDF) (TechRepublic)
Now with an application that contains embedded analytics, the marketing person can directly drill down into the reporting information embedded in the app without having to contact IT. This can be done through a self-service interface in real time.
“In one case, a manufacturer was trying to improve operational performance through the use of an application and set of stated metrics,” Schneider said. “Everyone had to log in to the application to record their metrics, but the overall goal of improving performance remained elusive. The manufacturer decided to augment the original application with an embedded analytics dashboard that displayed the key metrics and each team’s performance. This provided visibility to everyone. This quickly evolved into a friendly competition between different groups of employees to see who could achieve the best scores, and the overall corporate metrics performance improved.”
For most developers, embedding analytics in applications is still in early stages—but embedded analytics in apps is an area that is poised to expand, and that at some point will be able to incorporate both structured and unstructured data in in-app visualizations.
Best practices for embedded analytics
Companies and commercial enterprises interested in using embedded analytics in transactional applications should consider these two best practices:
- Think about the users of your application and the problems that they’re trying to solve
This begins with asking users what information they need in order to be successful. “Application developers can also benefit if they think more like product managers,” Schneider said. In other words, what can I do with embedded analytics in my application to truly delight my customer—even if it is the user next door in accounting who I see every day?
2. Start simple
If you haven’t used embedded analytics in applications before, choose a relatively easy-to-achieve objective for your first app and work with a cooperative user. By building a series of successful and high usable apps from the start, you instill confidence in this new style of application. At the same time, you can be defining and standardizing your embedded app development methodology in IT.
China and AI: What the World Can Learn and What It Should Be Wary of
China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. While the US still leads in absolute terms, China appears to be making more rapid progress than either the US or the EU, and central and local government spending on AI in China is estimated to be in the tens of billions of dollars.
The move has led—at least in the West—to warnings of a global AI arms race and concerns about the growing reach of China’s authoritarian surveillance state. But treating China as a “villain” in this way is both overly simplistic and potentially costly. While there are undoubtedly aspects of the Chinese government’s approach to AI that are highly concerning and rightly should be condemned, it’s important that this does not cloud all analysis of China’s AI innovation.
The world needs to engage seriously with China’s AI development and take a closer look at what’s really going on. The story is complex and it’s important to highlight where China is making promising advances in useful AI applications and to challenge common misconceptions, as well as to caution against problematic uses.
China’s approach to AI development and implementation is fast-paced and pragmatic, oriented towards finding applications which can help solve real-world problems. Rapid progress is being made in the field of healthcare, for example, as China grapples with providing easy access to affordable and high-quality services for its aging population.
Applications include “AI doctor” chatbots, which help to connect communities in remote areas with experienced consultants via telemedicine; machine learning to speed up pharmaceutical research; and the use of deep learning for medical image processing, which can help with the early detection of cancer and other diseases.
Since the outbreak of Covid-19, medical AI applications have surged as Chinese researchers and tech companies have rushed to try and combat the virus by speeding up screening, diagnosis, and new drug development. AI tools used in Wuhan, China, to tackle Covid-19 by helping accelerate CT scan diagnosis are now being used in Italy and have been also offered to the NHS in the UK.
But there are also elements of China’s use of AI that are seriously concerning. Positive advances in practical AI applications that are benefiting citizens and society don’t detract from the fact that China’s authoritarian government is also using AI and citizens’ data in ways that violate privacy and civil liberties.
Most disturbingly, reports and leaked documents have revealed the government’s use of facial recognition technologies to enable the surveillance and detention of Muslim ethnic minorities in China’s Xinjiang province.
The emergence of opaque social governance systems that lack accountability mechanisms are also a cause for concern.
In Shanghai’s “smart court” system, for example, AI-generated assessments are used to help with sentencing decisions. But it is difficult for defendants to assess the tool’s potential biases, the quality of the data, and the soundness of the algorithm, making it hard for them to challenge the decisions made.
China’s experience reminds us of the need for transparency and accountability when it comes to AI in public services. Systems must be designed and implemented in ways that are inclusive and protect citizens’ digital rights.
But a closer look at the dynamics of China’s AI development reveals the importance of local government in implementing innovation policy. Municipal and provincial governments across China are establishing cross-sector partnerships with research institutions and tech companies to create local AI innovation ecosystems and drive rapid research and development.
Beyond the thriving major cities of Beijing, Shanghai, and Shenzhen, efforts to develop successful innovation hubs are also underway in other regions. A promising example is the city of Hangzhou, in Zhejiang Province, which has established an “AI Town,” clustering together the tech company Alibaba, Zhejiang University, and local businesses to work collaboratively on AI development. China’s local ecosystem approach could offer interesting insights to policymakers in the UK aiming to boost research and innovation outside the capital and tackle longstanding regional economic imbalances.
China’s accelerating AI innovation deserves the world’s full attention, but it is unhelpful to reduce all the many developments into a simplistic narrative about China as a threat or a villain. Observers outside China need to engage seriously with the debate and make more of an effort to understand—and learn from—the nuances of what’s really happening.
Building a Discord Bot for ChatOps , Pentesting or Server Automation (Part 5)
Coding and debugging with Visual Studio Code
Open Visual Studio Code and press CTRL+Shift+P to enter the input window. Write “ssh” and select “Remote-SSH: Add New SSH Host…” for adding our server. It will ask you IP Address and the user of our Digital Ocean server
The app will show us the success message allowing us to connect directly
Once again press CTRL+Shift+P and enter “Remote-SSH: Connect to Host…” and select the connection
Now we will use the knowledge of the previous steps. Create the “.env” file with your secret constants, the “requirements.txt” file with the dependencies and the “bot.py” file with your existing bot’s code
To test it quickly we need a “.env” file with the “DISCORD_TOKEN” constant
A “requirements.txt” file like this one
And for the simplest bot code write this in the “bot.py” file
Go back to the terminal or use the integrated terminal in Visual Studio Code and install the requirements with the command
To test the bot write the command
You should see the “<Your bots name and id> is connected” message in the terminal and in Discord you should see the bot status as online
If you like to debug in Visual Studio Code to fix some bugs or to understand the logic, press F5 key in the IDE and select “Python File”
The IDE will enter debug mode allowing you to breakpoint the code and see the content of the variables
We are all set for this step.
If you encounter typos or something doesn’t work no more write me a comment and I will keep this guide updated. Last update June 28 2020.
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